Chatbots raring to read the room: AI sentiment analysis

Casual man relax chatting with chatbot via mobile smart phone application
(Image credit: Shutterstock / TippaPatt)

One of the key pillars to successful customer service is the ability to understand the customer – acting in accordance with their tone and mood is integral, especially when dealing with disgruntled customers.

Accurate sentiment analysis has long been a target for businesses aiming to improve their satisfaction levels, but conventional tools have begun to hit their limits. Insights that come from older varieties of sentiment analysis are sourced from biased examples of customer sentiment: reviews, feedback forms and social media do little to aid as customers seek out these with preconceived thoughts and feelings. Such tools are also limited by their basic language comprehension capabilities, failing to read between the lines and access customer sentiment with nuance.

However, natural language processing can reinvigorate sentiment analysis, developing less biased and more accurate data for agents and chatbots to utilize. With reliable customer sentiment data, AI-powered chatbots provide better customer service that is tailored to the customer's needs.

Prasad Ramakrishnan

CIO at Freshworks.

Taking appropriate action

Sometimes, customer requests may not require emotional analysis, but now and then it may be the difference between a terrible customer experience and a positive one. Take an example of a customer buying a bag from a retailer. Asking the question “What’s my tracking number?” may have a simple answer that doesn’t require tonal variety, but what if the customer’s order is delayed or cancelled?

In these kinds of situations, AI-powered chatbots can take action according to customer tone – offering remedial actions in the form of discounts, or preparing a repeat order or refund. Mending a deteriorating support situation has traditionally fallen to a human agent, but that sometimes led to delays in resolution according to employee availability that could negatively impact what would otherwise be a positive customer experience. By basing response tactics in customer sentiment analysis data, the decision to accommodate can be matched appropriately to the relevant level of response required, potentially reducing costs lost as well.

While AI-chatbots won’t completely replace human agents, global enterprises have customer bases expecting support around the clock, leading to a demand that isn’t always fulfilled by employee hours. Customers are looking for simple questions to be answered instantly, and aren’t satisfied with waiting for order updates or basic queries. Chatbots can provide instant response times that recognize the emotion or sentiment behind a human user’s words – and the appropriate moments to act on it.

Additional AI insights

Outside of direct customer support, sentiment analysis through AI chatbots could also provide valuable insights into customer behavior and brand performance. By harnessing the data already present, businesses can access better informed CX strategies, both in optimization of business processes and accessing more accurate sentiment analysis data of customer experiences than feedback through social media or surveys.

In addition, chatbots using sentiment analysis will be able to identify curious customers, opening up avenues to upsell through service interactions, while avoiding situations in which this would be inappropriate to the customer.

AI assisting agents

The future of customer experience is tied into AI adoption, and businesses looking to maximize their customer service will apply the insights chatbots can gain within early conversation in agent to customer interactions. By providing agents with a comprehensive report of customer sentiment before any messages are sent, chatbots can reduce friction before the conversation has even begun, leading to less situations where customers are further frustrated by repeating their circumstances or grievances.

When used in collaboration with humans to validate response suggestions and sentiment analysis, chatbots’ tone and responses can be improved on too. By tracking when humans grow frustrated with bots against when they’re satisfied, businesses will gain insight into the pain points that can push customers away from the chatbot experience.

The future of customer experience

As customer expectations continue to rise, businesses will need to refine their support processes to match demand. Natural language processors will continue to improve, chatbots will only get better at supporting customers and agents in their experience, and smart organizations will invest in their customer base through advanced chatbot tools. By taking advantage of chatbots and co-pilot AI technology, businesses can turbocharge their support and drastically improve customer satisfaction scores, leading to more smiles all around.

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This article was produced as part of TechRadarPro's Expert Insights channel where we feature the best and brightest minds in the technology industry today. The views expressed here are those of the author and are not necessarily those of TechRadarPro or Future plc. If you are interested in contributing find out more here: https://www.techradar.com/news/submit-your-story-to-techradar-pro

Prasad Ramakrishnan

Prasad Ramakrishnan, CIO, Freshworks. 

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