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Mass Communication-Can Bots Convey Empathy in Customer Interactions?B-AIM PICK SELECTS

Humans have always loved the idea of robots having feelings. Hollywood has cashed in on this affinity in multiple films, from making robots fall in love with each other, to an alternative dystopian future where robots are taught to feel, leading them to overpower humans. But even with such narratives, humans like it better when chatbots are taught more about feelings and made to assist them with empathy1.

Chatbots in customer service are used to optimize your customer experience and filter out basic how-to and level 1 questions. However, there are bots that are designed to do much more than that. No matter what the goal is for your chatbot, building it to deliver empathetic answers is crucial for any business.

When a conversation has a tone of empathy to it, the people or in case of chatbots, the person conversing with the bot will feel a sense of contentment. Though chatbots are built to collect data and assist accordingly, humans on the other side are trying to relate emotionally. Making chatbots converse with empathy helps with overall satisfaction in your customer support. Understanding human emotions also allow chatbots to deliver better customer service.

Empathy, however, branches into three types – cognitive empathy, emotional empathy, and compassionate empathy.

Though all three forms of empathies make users feel better than having robotic assistance that is strictly advice-only, compassionate empathy seemed to work the best of them all. See it for yourself – “That can be quite disturbing” works better than “I’m sorry to hear that”. The initial statement feels sincere while the latter sounds detached.

The second rule is to give options. When you ask a person “how are you feeling today?”, they probably are going to cut you off with an “I’m fine”, while absolutely not being fine. Paraphrasing it for the customer helps the bot to listen and understand the customer better. When you know a customer has had a bad experience, giving them options to choose from “Actually, I felt really bad” or “I’m feeling better now” can give a better peek into their feelings.

The above image shows how active listening, empathy, and sympathy can be used to help a frustrated user to feel better.

Now that we’ve seen how empathy makes chatbot conversations better, let’s see how developers are enabling chatbots to empathize and learn the human way of thinking.

Natural Language Processing

Chatbots no longer need to be described as robotic, thanks to the development of Natural Language Processing (NLP). This technique has made chatbots understand the nuances of how language works, with a set of detailed text-based commands, helping them understand what is being asked and generate relevant answers.

In short, NLP organizes human language in a structure that is understandable for the chatbot’s system. This structuring takes place under the basis of phrases, grammar, and syntactic analyzation.

After understanding a sentence, the NLP plans and puts out linguistically correct phrases as responses.

NLP also employs text analysis to understand the sentimental outcome of a customer’s message. They are classified into negative, positive, mixed, and neutral to identify user behavior and how to respond to customer queries in the future. This technique also helps brands to identify what features customers like the most, and what are the critical trouble points.

A great example of efficient chatbots built using a custom NLP model is Niki. Niki is your one-stop-shop conversational commerce bot. The bot tips you off with the best offers on anything from booking hotels to paying utility bills.

Deep Learning

Deep learning is a hybrid of NLP and machine learning. It uses neural networks to make machines learn a desired feature with a vision based memory. For example, differentiating the pictures of trains from cars. Below is a Venn diagram of where deep learning lies in terms of NLP and machine learning.

Deep learning has been used in chatbots and has successfully mapped customer emotions and responded accordingly.

Research scholars in Tsinghua University2 fed a data set of 23000 phrases, each of them tagged to an emotional tone. The chatbot was not only able to analyze the conversation with a human and detect the sentiment of the conversation but were also able to come up with relevant and appropriate answers.

One such chatbot built using deep learning is Replika3. If you thought Siri or Alexa were friendly enough, Replika makes you rethink. This bot was created to help people with anxiety by making friendly conversations.

The app also allows its users to track their mood based on the conversation and provides insights to their personalities for self-reflection.

Artificial Intelligence

Artificial Emotional Intelligence is a field that goes beyond chatbots. Emotion AI primarily uses facial recognition and speech recognition to understand emotions. Researchers use everything from body language, facial expressions, tone, and gestures to read what the person is feeling. In fact, scientists have been able to simulate sensory feelings of heat and cold in machines.

In chatbots, emotion AI is handy when the bots have to identify relevance and urgency. For example – when a person says “I’ve to pee!”, an emotionally equipped AI would be able to identify the urgency of the situation and make real-time decisions. Thus, an AI chatbot would answer with directions to the restroom even when a question wasn’t asked.

Through smart customer segmentation and analyzing it with predefined customer choice model, Amadeus4 has come up with a way to personalize suggestions for travelers looking to book tickets to their dream destinations.

Are Chatbots Finally Taking Over Human Conversations?

We all have come across those hysteric conspiracy theories on how AI might overpower the human species. But in reality, AI can only assist humans at a better pace than what it did in the past. Machines are still yet to understand the different ways a same word can be used. In one such case, when a passenger messaged a Canadian aircraft support chatbot5 about how thankful she was that they could transport her on time for a “plant cutting” event, the chatbot directed her to a suicide prevention hotline after detecting the word “cutting”

Another major hurdle is that no chatbot research has been able to build a chatbot that could remember its previous interactions with the customer and reply with context.

Wrapping Things Up

Emotionally intelligent chatbots can be of great use across fields, especially in customer service. But there are still limitations, and bots cannot replace humans. Emotionally intelligent chatbots, however, can do the following tasks more efficiently than ordinary bots:

– Walk customers through what the company does – Clear basic doubts in the product, direct them to FAQ/knowledge base – Do basic functions on behalf of the customer – books tickets, assist in banking – Perform a single function – tell weather, suggest restaurants/ recipes

The most logical way to ace your customer service game is by integrating both human operations and chatbot assistance and know when to use them. Freshdesk’s omnichannel helpdesk is one way to start this journey.

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