Conversational UI first attracted mainstream attention back in 2010, when Apple introduced Siri to iPhones across the world. Within months, digital users of all ages were using their voice assistants to write emails, initiate Google searches, write texts and schedule notifications. Siri changed the way consumers interacted with technologies and businesses forever. Soon, everyone from Google to Amazon and Microsoft was1 following suit, releasing AI-enabled tools that allowed individuals to talk to machines as if they were people.
In a world where real-time messaging has become our primary mode of communication, these platforms offered the perfect solution for businesses looking to increase customer engagement across the buyer’s journey. With most Internet users admitting that issues like unintuitive navigation, inadequate communication, and a lack of business information significantly impact their enjoyment of a particular website, chatbots gave businesses the ability to answer common customer concerns and guide their online experiences naturally and cost-effectively.
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In 2017, many of these promises came to fruition. Over the course of the year, Facebook introduced new chatbot capabilities to its Facebook Messenger system which allowed members to discover and interact with thousands of businesses through their chatbots. The social network also expanded their chatbots to other areas, offering businesses plug-ins to host chatbot messengers directly on their websites. Meanwhile, Microsoft integrated chatbots into its popular CRM platform Dynamics 365 giving businesses the ability to push chatbots into their existing customer service workflows. Other chatbots like Shopify’s Kit and FirstJob’s Mya, helped to streamline and optimize a range of business processes from marketing and advertising to recruitment.
Chatbots are just getting started. AI today is only just beginning to unlock the vast potential of NLP and deep learning to enable more customer interactions and operational capabilities. According to media agency Mindshare UK, 63% of people are willing to use chatbots to converse with businesses and brands today while at least 27% of the world’s population is predicted to be using chatbots by 2019. Accenture estimates that the market for chatbots in the US will triple to $1.86 billion over the next couple of years alone. Whichever way you look at it, we’re entering the age of chatbots. Here’s a glimpse of what lies in store.
As businesses integrate chatbots across their websites and social media profiles efforts are being made to centralize all conversations under one umbrella. So that when users ask a question on Facebook and are directed to your website, the website chatbot can take over the conversation and pick up where the discussion left off. This relieves customers of the frustration of repeating the same talking points over and over again on multiple platforms.
A recent Oracle survey revealed that at least 80% of brands are planning on implementing Chatbots in their customer service functions over the year. These indications aren’t just coming from established Fortune 500 companies either. Travel agencies, small businesses, healthcare providers and telecommunications firms are all looking to use chatbots to enhance their front-end.
Chatbots may also hold the key to extracting insights from big data. While analytics software and BI tools have been a firm fixture in corporate environments for years now, non-technical executives still struggle to get the most out of these applications. Newer chatbots are being developed with powerful AI capabilities that could allow them to turn deep learning towards understanding business processes across the enterprise. Armed with these new capabilities, executives will be able to converse with their analytics platforms in a human manner to extract the strategic insights they need.
As digital adoption increases across every organization, many businesses are running multiple critical applications. For employees, the increasing technological complexity can act as a significant barrier to productivity, as they have to switch back and forth between different interfaces and understand how to access and use each one. Chatbots could act as a natural link between these diverse applications. With, users would be able to manage tasks, logins, updates, and information gathering through a single conversational platform.
One area where chatbots have traditionally fallen short is in understanding the intention and emotions of different users. This deficiency has largely relegated chatbots to first-line customer support until now. By adding a sentiment analysis layer to the bots natural language processing engine, chatbots will be able to extract key phrases and words from the user message and compare them to a database of terms that are weighted by their emotional sentiment. This helps the bot to develop an understanding of the customer’s mood, allowing it to change its messaging accordingly.
For years, sentiment analysis has been used in politics and marketing to understand public perceptions of certain topics. Armed with these insights, businesses are able to adjust their communications to better suit prevailing attitudes. In a chatbot, these same capabilities can be used to read positive or negative emotions in real-time and to adapt replies accordingly. If a customer seems particularly escalated, the chatbot could even pass the user over to a live representative for more in-depth assistance.
If this technology pans out the way users predict then organizations will eventually be able to cut down on increasingly costly call center departments. Instead, these centers could be limited to a small cadre of expert call center agents that are able to tackle more advanced customer concerns.
Instead of trusting users to navigate new software on their own, app developers are integrating conversational platforms into their products. In-app chatbots can help answer urgent user queries, deliver information about updates and changes, and aid navigation.
Recently, many event organizers have begun to integrate chatbots into their life experiences. A chatbot-equipped app could be used to deliver information and personalized assistance to attendees in a number of ways.
All these Chatbot trends won’t happen out of a vacuum. There’s still a lot of changes on the future development of NLP and other bot applications that still have to wait for more mature technology to cut in and stabilize it. So do keep this in mind: don’t jump in and rush to getting all things started before the big companies do. Just sit tight and patiently wait for the next move that other tech giants do before making yours.
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