Saturday, October 24, 2020

Reinvent your customer experience with conversational AI

Wazzup Pilipinas!

The COVID-19 pandemic has considerably changed the way organizations operate. During a time when many businesses are struggling to survive, it has become more crucial than ever to be able to differentiate your business from the competition. While this means different things to different organizations, one factor that remains constant across industries is the adoption of digital solutions to improve customer services and support.

Enhancing customer experience has become the number one priority for organizations across the globe; and in order to fulfil this goal, many businesses are turning to chatbots as a first line of response in customer communications. Well-planned chatbots are an excellent way to extend fast, personalized, and scalable conversational support. From booking movie tickets to setting up clinic appointments, the scope of today's virtual assistants has grown by leaps and bounds.

Like most other countries in the region, companies in the Philippines are beginning to realize the value of the technology. Though, according to Kearney, a U.S. based consultancy firm, the investment in Artificial Intelligence (AI) per capita is poor (less than $1), as much as $92 billion could be added to the country's economy (12 percent of its expected 2030 GDP) by embracing the technology more.

Furthermore, given the fast-paced, technologically advanced world we live in, customers expect nothing short of instantaneous, highly personalized services. Almost every interaction these tech-savvy customers have with businesses is digital, and they expect their queries and concerns to be addressed in an immediate, hassle-free manner. Thus, the truly revolutionary future of perfecting customer experience lies in the hands of virtual assistants.

Investing in customer relations

Great businesses are built on the foundation of great relationships they build with their customers and great relationships are built on accountability and transparency. Thus, maintaining a steady channel of communication with your market is of utmost importance. However, providing round-the-clock customer support can be an extremely resource intensive process. Thankfully, virtual assistants can make this job a lot easier.

Advancements in natural language processing and speech recognition technologies have given rise to powerful chatbots that can parse massive amounts of text and learn the best ways to enhance customer service operations. Apart from the strength of their features, chatbots are also known for their adaptability. They can be easily integrated into popular messenger applications where people spend much of their time online. Beyond mobile and web interfaces, conversational interfaces are gaining traction, and customers will soon be able to choose seamless conversational interfaces across products.

These conversational assistants can be used in nearly every aspect of your customer relationship management process. They can act as personal assistants for your customers, readily available at their beck and call. They can also help your customers troubleshoot issues, provide self-help information guides and triage tickets, thereby enabling your customer facing teams to prioritize and attend to the most pressing concerns, while the users with less urgent problems are aided by the virtual assistant itself.

An AI-powered agent model

While the customer facing chatbots can directly interact with the customers, these virtual assistants can be of immense value to the customer service agents, as well. Besides handling a chunk of the workload for an overburdened customer service team, AI assistants can assist agents by providing all the necessary information they need before reaching out to the customer. They can act as the first line of defence in customer services, capturing critical information, and reducing the time it takes to get the required process initiated.

Chatbots can further help agents by not only suggesting specific actions after a ticket has been raised but also anticipating customer needs by learning from previous chat histories, preferences, and context provided. They can thus suggest pre-emptive actions by forecasting customer needs. Furthermore, they can also be integrated into the automated workflows of organizational processes.

Well-designed virtual assistants can also map customer queries and issues to the agents with the right skill sets. This not only helps in optimizing agent handle time, but also minimizes the possibility of escalation events and improves first call resolution rates. A powerful conversational interface will make the handoff from the bot to the agent so seamless that the end user will never notice the transition.

The future of conversational AI

Most of the present day chatbots are built on rule-based systems combined with natural language processing abilities. The fallibility of many of such virtual assistants lies in the fact that if the customer does not provide a clear message with a specific intent, the chatbot will not be able to provide the required information. Additionally, when faced with a query never seen before, the chatbot falters. Natural language processing capabilities give chatbots the ability to process the text in hand to identify the named entities and general intent the query contains, provided they follow a specific pattern. This is where language models come in.

Language models take natural language processing one step further by incorporating contextual understanding, known as natural language understanding. Language models not only identify the meaning of individual words, but also understand the context of a query. Thus, when faced with an unprecedented query, the chatbot can still process the contextual meaning of the sentence and present the likeliest response.

Natural language-based virtual assistants can thus hold conversations with the customers by keeping track of various contexts. A lot of research is going on to make bots sound more like human, including research on mixing code (mixing two languages during conversation) and evaluating the sentiment of the interacting human and responding appropriately.

These deep learning methods have given rise to many language models, such as the GPT-3, which can produce increasingly human-like text. The future of conversational AI thus shows immense promise, with further innovations in the field making it a worthy cause for investment.

By: Priyanka Roy, product consultant, ManageEngine

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