80% of businesses are expected to have some sort of chatbot automation by 2021.
The year 2020 has seen an unprecedented rise in the use of chatbots. Amidst the uncertainties caused by the pandemic and changing expectations about how brands should communicate with their customers, businesses have quickly adopted AI-powered bots to reduce the burden of their support staff and deliver easy, interactive, and more meaningful engagement to their customers.
No wonder chatbot technology has evolved to incorporate some powerful functionalities that will define the future of customer experience.
Research by Business Insider says, The global chatbot market is anticipated to reach $9.4 billion by 2024.
So, let’s have a look at the seven advanced chatbot features to consider in 2021.
Augmented reality (AR) in chatbots opens a world of immersive, personalized, and engaging shopping experiences for customers.
Gartner defines augmented reality as the real-time use of information in the form of text, graphics, audio, and other enhancements integrated with real-world objects.
POND’S, a popular skincare brand, launched a skin-diagnostic chatbot called SAL to assist consumers in dealing with common skincare problems across four areas – uneven skin tone, pimples, wrinkles, and spots. The bot leverages AI and AR to get an in-depth insight into the skin type and recommend suitable products. Customers need to simply upload a selfie, fill in a short survey, and the bot delivers a personalized skin diagnosis and product recommendations in less than a minute.
Such unique experiences generate buzz around the brand, boosting customer engagement and driving revenue in the process. Therefore, augmented reality will be a significant chatbot feature to consider in 2021, primarily for industries where buyers prefer a look-test or visual inspection of the product.
As the COVID-19 pandemic brought a wave of anxiety, confusion, and uncertainty, organizations recognized the increasing importance of responding to customers with empathy.
Sentiment analysis, therefore, becomes one of the most critical capabilities in a chatbot. Since tone and emotion significantly alter what a customer wants to convey, sentiment analysis allows bots to identify and understand the type and intensity of a customer’s sentiment, including anger, joy, fear, and frustration.
By deciphering words and sentence structures and extracting emotion, the bot can steer conversations, change the tone, or bring in a human agent for support. Hence, emotional intelligence will be a significant feature to look out for in bots in 2021.
Another advanced feature that is fast-changing the world of bots is text-to-speech technology. This technology allows brands to develop a voice of their own by enabling bots to speak in a fluid, natural-sounding, human-like voice.
With text-to-speech bots, organizations can provide more engaging, accurate, and quick conversational IVR support.
So, the next time a customer wants to book a hotel room, he/she just needs to call up the contact center and say, “I want to book a hotel room,” instead of going through multiple IVR options. The bot will ask for other details in a human-like voice, book the hotel room or directly route the customer to the next available agent.
Additionally, bots may leverage speech-to-text technology to transcribe audio to text in different languages and variants accurately. In fact, research by Gartner suggests, “by 2023, 25% of customer interactions will be via voice.”
Many organizations have started leveraging Microsoft’s Azure Cognitive Services to convert text to life-like speech or convert spoken audio to text in more than 100 languages and variants.
Despite chatbot technology growing at a rapid pace, in some situations, bots aren’t capable of handling customer needs entirely, and the conversation may require an agent handover. A customer may be angry or irritated, the issue may be complicated, or the conversation may involve high-value transactions with a customer at the risk of churning.
A few key chatbot capabilities that will ensure a smooth handover include –
Training, calibrating and explaining AI-enabled systems requires human-in-the-loop architecture.
Chatbots will come with a human-in-the-loop system to continually learn and become more intelligent. Small customer feedback, such as “click here if you are satisfied with the service,” can improve the machine learning algorithms and train the bot.
In addition to customer feedback, agent training plays a crucial role in enhancing bot performance. Contact center agents can classify outliers and exceptions, modify training data, and influence bot behavior.
Robotic Process Automation, or RPA, uses AI and machine learning to perform a variety of repeatable tasks, such as calculations, data entry, handling queries, etc.
RPA-chatbot integration is a powerful combination that can solve significant operational and workflow related issues for organizations. The automation capabilities of RPA combined with the cognitive abilities of chatbots can help enterprises automate processes end-to-end and reduce costs.
An RPA-enabled chatbot can integrate with multiple siloed and legacy back-end enterprise systems. RPA enables bots to retrieve information from such systems and handle more complex requests at scale.
Thereby, chatbots will not only handle queries and find information but also perform transactions on the user’s behalf, going from mere conversation to action.
Finally, the natural language processing capabilities that empower chatbots to understand the conversation context in multiple languages is an essential feature to consider.
Bots will be able to identify the intent of a query to provide a quick response and proactively seek information, ask clarifying questions, and confirm intent, even if the interaction isn’t linear.
Chatbots have gained traction owing to their ability to provide real-time, on-demand resolutions that consumers are increasingly seeking out.
In light of their growing popularity, organizations must look out for specific features that enhance chatbot capabilities and enable them to deliver engaging, personalized, and more human-like conversations to users.