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Creating Chatbots and Virtual Assistants That Work for Enterprises

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Ashely John

While many of us still wonder about the concept of Artificial Intelligence (AI), a majority of enterprises have already been thriving with sophisticated applications of AI. What we know as AI in general terms has come to the businesses as AI chatbots and Virtual Assistants today. As of now, the AI-based startups are one of the most funded ventures. In fact, many venture capitalists have been showing some skepticism about funding the startups that are not using AI in some form in their operations.

According to a Business Insider study, 80% of the businesses will adopt AI in some form by 2020. Besides, some studies have also revealed that Fin-tech businesses are one of the most active adopters of AI technologies, where they intend to automate 90% of their customer support using the same. These businesses have calculated that AI-based customer support will help them to save over $8 billion annually.

If you have been thinking that AI chatbots and virtual assistants are equivalent, stay right there and brush up your concepts by reading this article. Unless you have a clear understanding of both concepts, you cannot make an informed decision by their applications in your business. Both AI chatbots and virtual assistants are the most valuable products of AI, and they help enterprises in different manners. Chatbots, on one hand, is automating business processes, while virtual assistants are influencing the personal lives of the users.

Chatbots are AI-based software solutions that businesses use to automate different human interactions. Live chat customer support is one such application of AI chatbots. The role of AI is to put machine-learning technologies into action for learning human behaviors in customer support systems and automating the response processes. Customers interact with the chatbots to resolve grievances, ask questions, and raise certain concerns. The chatbot, which works in harmony with CRM systems, can put the data into analytics and reply to the customers accurately and quickly.

A virtual assistant is yet another important application of AI that supports users in performing daily tasks like setting up the alarm, booking appointments, reminding of upcoming events, sending messages, and much more. These are more of a replacement for human assistants; say, when you ask your PA to take some notes or send an email to someone.

· Feelings and contexts:

Traditional chatbots are not good at understanding human contexts. They can offer accurate and quick responses to the data extensive queries, but they lack an understanding of the human moods and sentiments. Virtual Assistants possess a deep application of Natural Language Processing (NLP), which they pair with machine learning to interact in a way more as humans do.

However, with certain advancements in AI, we have been able to develop some chatbot virtual assistant solutions that use NLP and deep learning. They not only understand human contexts and patterns better than normal chatbots but also communicate like humans.

· Continuous-flow in superseded conversations

Chatbots generally lose context if you break the conversation. They do not maintain a conversational flow in irregular and broken interactions; bots cannot remember the context of an interaction. Whereas virtual assistants rely on dynamic conversational flow. They remember past interactions and use the data from them to understand human contexts better.

We have been able to create some AI chatbots like Facebook messenger bots that understand conversational flows better than regular chatbots. These special bots can remember previous interactions and offer responses that are more accurate the next time they encounter a similar situation.

Both technologies rely heavily on concepts of Training, Machine Learning, and Deep Learning to work. Enterprise AI chatbots, which use NLP and NLU, are as quick as chatbots, and as efficient as virtual assistants.

Enterprises can automate their internal operations by integrating enterprise chatbots in their human-led operations. They can streamline internal processes, such as recruitment, resume short-listing, replying to employee queries, scheduling tasks, logging attendance, managing leave registers, flagging certain behaviors, and much more.

Similar to internal interactions, chatbots with NLP and NLU capabilities can streamline the external business processes too. They can manage the transactions with vendors and different suppliers, generate invoices, process refund requests, and clarify B2B queries. The NLP technologies can help to share excessive loads from email tools and process most of the communications through integrated channels itself.

Customer support is probably the most common application of chatbots. However, with the introduction of deep machine learning and NPL in the chatbots, the customer support systems have gone even better. Live chat solutions are working in coordination with AI bots and offering even better experiences than their human counterparts offer. Take data extensive queries for example. A human executive cannot offer a faster response than an AI chatbot, which you have integrated with your CRM solution. The chatbot virtual assistant can look deep in the CRM database and offer quick replies to data extensive queries, such as order status, payment status, and stock information, etc.

Paying the bills is a tedious task in both B2B, B2C, and C2B environments. Whether a business has to make payments to its vendors, or a customer has to pay a bill to a business, the traditional process relies on loads of paper trails, invoice generation, and manual payments through net banking or writing checks. However, today, AI chatbots are working in coordination with messenger applications and mobile payment solutions (like Google Pay), which automate or schedule payments and generate invoices without any paper trail.

Chatbot virtual assistants can reach out to your prospects as efficiently as the traditional marketing channels. They can manage your live chat support, schedule email campaigns, manage WhatsApp business account, send Facebook messages, and trigger automatic push notifications without any manual intervention. The chatbots with messenger applications and marketing tools like WhatsApp, Facebook Messenger, Instagram DM, Slack, push notification tool, and email-marketing tool can automate most of the digital marketing processes.

As per the sales generation is concerned, the same chatbots can use deep learning to analyze your sales channels and customer behaviors and push personalized recommendations. They can trigger micro-personalized cross-sale and up-sale pitches where customers would be more likely to have an interest.

Businesses need feedback from both the internal and external sources to improve themselves. The traditional channels like survey forms and email have done their jobs quite well. However, now, the Ai chatbots are streamlining the entire process. In fact, you don’t even need to launch dedicated feedback collection campaigns. The bots can trigger Q&A, quizzes, and polls within the regular streams and collect real-time responses without much intrusion. With proper integration of data analytics, the same bot can also analyze the feedback and produce graphical reports in real-time.

No doubt, chatbots, and virtual assistants possess extended prospects in the enterprise business applications, but they can’t do anything valuable until they have data. Data is the primary fuel for AI chatbots and Assistants. For proper implementation, you must train your chatbot and virtual assistant by feeding as much data as possible. For that to happen, you must open the doors of your CRM and other data sources. The more it feeds, the more is the chance to eliminate nuances from data, filter out meaningful insights, and make accurate conclusions.



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