A chatbot is a software program that can simulate conversations with a human through a text-based message during a chat.
The ideal ai chatbot should be able to convince the user that they are communicating with another human.
The idea behind the ai based chatbot was to keep the user engaged until the next customer service representative was available. But other operational uses also established chatbots as one of the key differentiators in the entire customer experience journey.
the ai based chatbot adoption rate is increasing as companies scale their customer base. With limited resources for customer service, chatbots offer a lot more value than traditional methods in terms of 24/7 availability, reduced operating costs, better documentation, and more.
IDC (International Data Corporation) reports on the conversational AI market that spending on cognitive systems and AI will reach $77.6 billion in 2022. In comparison, the 2018 report suggested a market size of $24 billion.
The increased spending on chatbot suggests that this market will continue to grow as companies adopt chatbot for internal and external use cases.
You, too, must have come across a Conversational AI while consuming, searching, or complaining about a service from an enterprise.
A Brief History of Chatbots
Although conversational AI is the buzzword today, the first Chatbot was introduced even before the launch of personal computers.
In 1966, Joseph Weizenbaum created ELIZA at MIT. It took keywords and inputs and shared an output based on pre-configured rules.
Next was ALICE by Richard Wallace in 1995. It won 3 Loebner Nobel Prizes but couldn’t pass the Turing test.
Modern chatbots came after the digital revolution, and smartphones popularized chatbots as virtual assistants such as Siri, Google Assistant, Bixby, Cortana, etc.
When looking through the lens of running business operations, the need for conversational AI is duly justified.
When augmented with RPA, Machine learning, and Natural language processing technologies, conversational AI can take up additional responsibilities and serve many use cases. Let us look at some of the best use cases of Conversational AI.
According to Gartnerup to 70% of white-collar employees will engage with a chatbot daily by 2022. The chatbots help in automating mundane tasks and support the workforce to focus on more strategic tasks.
Why need a conversational AI?
Cost of Operations:
Running a contact center 24×7 involves running 3 shifts of 8 hours each. If the call volumes are low during a particular shift and require a significantly less number of agents to handle the customers, the entire office has to be functional.
Brands do not risk losing a customer; hence, they need to pump in more money to run 24×7 operations. With chatbots, there would be no need to run the office for all 3 shifts, and there will be considerable cost savings.
In addition, Conversational AI platform further reduces the need for upfront payment.
The customer with spending power defines the way a market develops. In this case, the millennials with the highest spending power are the most avid users of chatbots for a quick resolution.
According to Forbes, 60% of millennials confirmed their dependency on chatbots for customer support. In addition, 70% of the millennial chatbot users had positive experiences with the chatbots.
These positive experiences bolster the trust in a brand and increase the conversion rate.
Enterprises should look at chatbots as revenue generators and use them to create positive experiences with their target audiences.
Increased Workforce Productivity:
For high-growth startups and enterprises that want to scale faster, workforce productivity is paramount.
While investors can provide capital, no investor can buy more time. The bandwidth crunch calls for the prioritization of strategic work over mundane operational work.
Chatbots can help employees by overtaking operational tasks and assisting the workforce.
ace per a sales force study64% of employees can now focus on the bigger picture rather than performing repeatable operational tasks.
Automated Customer Queries:
One of the best abilities of conversational AI is to provide 24×7 real-time support to customers. Customer queries and inquiries can be automatically logged through Conversational AI.
Since the customer ID is also recorded, chatbots can respond to individual users at their disposal.
For example, during customer onboarding to a platform, the customer might have multiple questions about service level agreements, personal details, privacy options, and more. Chatbots can answer such questions, and most low-level customer calls can be hindered.
NBX (Norwegian Block Exchange) utilized chatbot automation for customer onboarding and automated 90% of tickets through a chatbot.
E-commerce Conversational AI:
While other industries also benefit from chatbots, e-commerce has popularized the use of conversational AI.
In the absence of a seller’s physical presence, chatbots have become the de-facto method of communication for e-commerce platforms.
AI-enabled chatbots help in customer satisfaction, leading to a better shopping experience for customers.
They are the perfect assistant that keeps track of the entire journey providing support during and after the shopping. In addition, parcels can be tracked with the help of chatbots.
CIOs at chatbot-enabled e-commerce platforms can vouch for an increase in metrics such as Average Order Value and Customer Lifetime Value for a user.
Chatbot is much better than the old FAQ sections. They supply direct answers to the requested information.
Chatbot also present relevant options to customers to choose their journey. Also, they help supply customer support by providing essential troubleshooting functions.
If the chatbot can resolve the issue, real-time interaction with a customer will provide a better experience and recall value.
Shambhavi Sinha is working as an SEO expert at Ameyo. She also likes to write tech-based stuff. Her aim de ella is to provide knowledge to users by sharing the knowledge about the latest trends about contact centers.