Artificial intelligence powered Chatbots are essentially software applications that possess human traits such as human communication, interaction and emotion. In essence, Chatbots offer a conversational experience leveraging artificial intelligence (AI) and natural language processing (NLP) to mimic conversations involving real humans.
By becoming the channel between the brand and the customer, Chatbots have the potential to enhance the customer experience, by interacting with them through different customer engagement mediums, taking data inputs and sharing data outputs in those mediums, with the help of various APIs. By deploying chatbots, enterprises can automate and enable swifter real-time interactions, with information at the fingertips and enabling customer service agents to secure ready help from bots.
Trends underlying Chatbots becoming mainstream
Just like other disruptive technologies, the rise of chatbots to the mainstream could be traced to a number of sweeping changes imparted by technological forces transforming the world in parallel. Whether it be progress attained within the field of Artificial Intelligence (AI) and the way we leverage technology to connect with the world around us, there are several factors at play:
Gen Y and Gen Z extensively using messaging apps: With the rise of the smartphone as the overwhelmingly primary communication device for the youth, messaging apps and social networking platforms became mainstream. Consider, for instance, Whatsapp that in 2015, breached the billion user mark. In fact, social network usage has declined, and replaced by the rise of one-to-one communication platforms in the form of messaging apps like Whatsapp.
Such one-to-one messaging platforms on smartphone have contributed to the rise of chatbots.
Pleothera of Smartphone Apps: Smartphone apps have skyrocketed with plenty of app choices available for consumers. From a consumer perspective, its overwhelming and confusing to depend on apps. If not in the immediate future, chatbots still are on track to replace apps over a period of time.
Technological forces (AI, ML and NLP) making perfect pitch: Technological progress made by AI makes the conditions right for chatbots to come to the fore. AI, and associated technologies, such as machine learning, natural language processing, image and voice are becoming mature, and with indications that it will cross the $5Bn milestone by 2020.
Consumer-First, and CX becoming key focus: With the rise of messaging platforms and digital contributing to bridging the gap between consumers and enterprises, consumers have become more demanding than ever before, and impatient enough to not call the helpline for simple tasks. Enterprises are paying attention to this aspect of customer experience, and making seamless assistance available to them through specialized chatbots.
Use Cases for Chatbots:
Product Suggestions: For consumers who are impulsive and yet discerning buyers, the chatbot is a boon, as it offers new product recommendations based on user likes, preferences and dislikes.
Customer Support: 24/7 unrelentless and sophisticated customer service contributing to enhanced customer experience is key for businesses. Whether it be an online hospitality marketplace, such as Airbnb, or even a productivity tool like Evernote, the usage of chatbots on social media networks to provide 24/7 customer service, including answering and addressing customer complaints, or simply tracking order status.
Financial Market Access: Chatbots enable easy trades, get notifications about stock market trends, track personal finances, or get help in securing a mortgage. For instance, some banks user AI-powered chatbots to allow users to check their personal and investment accounts and recommend new investment opportunities.
Meeting Scheduling in Always-On Workplace: In a
In always-on workplace where users are always on the move, it becomes tough to get everyone on board for a common meeting. That’s where a chatbot can be helpful in making it all work for users.
How do Chatbots work?
Chatbots can work in mainly two ways, rule- based and machine learning- based.
When it comes to rule- based chatbots, the nature of interaction is such that when a customer accesses the chatbot with a query, it recognize the keywords in the input and then accesses a pre-set database to give a predefined response. Rule-based chatbots are akin to the IVR of the yore.
On the other hand, machine learning-based chatbots possess some level of human intelligence, and are adept at not just taking instructions, but In this case, it uses the same rules as of an IVR or web self-service.
The future of chatbots
The chatbots of the future would be more evolved and armed with competence to solve complex tasks daily without the need for human guidance or intervention.
Hyper-personalization will define the future, with chatbots working overtime to understand users more closely, and learning from continuous interactions to predict, improve, resolve, as well as personalize responses. Unlike today’s chatbots that offer a simplified set of responses, the future chatbots will be more responsive and more personal.
The key success metric for chatbots would be swift and accurate problem resolution with minimal or no need for users to explain problem in great detail. Those chatbots that are able to achieve this would be the ones to beat.
The focus of the chatbots of the future will be on leveraging data from multiple touchpoints, including from within and outside the enterprise, to put together a rich knowledge set for users.