5 Surefire Ways to Boost Customer Satisfaction with Chatbot Sentiment Analysis

Chatbots, or conversational bots, are transforming how brands interact with their audiences. They allow businesses to identify user preferences, moods and manage the flow of interaction keeping their sentiments in mind.

But how are chatbots able to do all this?

With the help of the sentiment analysis feature.

Sentiment analysis, powered by ML (Machine Learning) and NLP (Natural Language Processing), enables chatbots to pick up on human emotions during ongoing conversations. As per reports, chatbots can handle up to 80% of customer queries a business receives, significantly reducing the load of customer service reps.

Sentiment analysis allows chatbots to push the boundaries of customer service even further. It enables them to offer empathetic, and even contextual, service to website visitors, whether they’re prospective buyers or even repeat customers.

This blog will give you tips on how to leverage the technology to its full potential. But before that, let’s learn more about chatbot sentiment analysis.

What is chatbot sentiment analysis?

Sentiment analysis empowers chatbots to identify human emotions from their textual and audio inputs. It understands user intent by extracting ideas, opinions, or sentiments through their conversations.

What’s more — the sentiment analysis feature allows chatbots to analyse the user’s mood based on sentence patterns and linguistic signals. This approach helps chatbots tailor replies accordingly, ultimately delivering better responses and enhancing customer satisfaction.

How does sentiment analysis work in chatbots?

When a chatbot with sentiment analysis is deployed to make a conversation with the user, it first identifies the sentiment and the emotion behind their responses to check if the mood of the dialogue is positive, negative or neutral.

Machine learning and natural language processing work in collaboration to detect the magnitude and nature of the emotions that are being conveyed and give out a numerical score.

Once the chatbots receive these scores, they’re able to drive the conversations in the right direction.

For example, if the sentiment analysis gives out a positive score to a conversation, then the chatbot uses the interaction as an opportunity to recommend a product to the visitor.

Conversely, if the score is negative, the chatbot can transfer the conversation to a human agent who can understand the complexity of the issue and offer empathetic responses and compensations accordingly.

What are the benefits of incorporating chatbot sentiment analysis in your support staff?

Chatbot sentiment analysis is an excellent tool for businesses to understand their customers’ mindset and consequently take appropriate actions.

All customer-centric industries — e-commerce; banking; hospitality; healthcare; travel, etc. — can benefit by integrating chatbots with sentiment analysis.

Some of these advantages include:

• Accurate responses: Chatbots identify if a customer’s mood is positive, negative, or neutral. Consequently, they offer relevant responses to meet customer expectations
• Solve common customer queries: AI chatbots can integrate machine learning (ML) and natural language processing (NLP) to give numerical scores to emotions like anger, happiness, and frustration, etc., and address everyday queries effectively
• Stellar customer experience: Chatbot sentiment analysis helps brands understand the customer journey at all touchpoints and fix issues arising at various stages accordingly
• Improved customer engagement: Chatbots adapt to the customer’s mood and steer the discussion appropriately, enabling augmented customer engagement

5 powerful tips to improve customer satisfaction with chatbot sentiment analysis

The efficiency of sentiment analysis-powered chatbots can be used to offer an excellent customer experience. It evaluates customers’ tone and responds suitably, resolving issues itself; redirecting them to a human agent for more complex issues, or just upselling and reselling.

Businesses can use chatbot sentiment analysis to boost their customer satisfaction rate in a variety of ways.

Accurate customer categorisation

Chatbots are a pro when it comes to collecting customer data and insights by recording the entire conversation. With sentiment analysis, they are able to identify satisfied and frustrated users within your customer base.

Being able to draw this distinction helps them segment your audience. This allows you to effectively prioritise support for customers who sound as if they are at the risk of churn. You can offer them discounts, deals or even a replacement if need be.

To the segment of customers who are pleased with your products and services, you can deliver new recommendations, loyalty programme memberships, and other such incentives to keep them coming back.

Enhances engagement

Emotions play a huge role in a buyer’s purchase decisions. One of the most favourable benefits of chatbots with sentiment analysis is that they can decode the user’s mood and then personalise responses.

This feature ultimately helps chatbots hold interactive conversations with users. Additionally, they enhance engagement even for leads, and not just existing clientele.

Let’s say, for instance, a potential customer visits your website looking for a specific product. A chatbot can then engage with them, asking for their requirements, suggesting products or alternatives that may fit their needs, recommending newer models or upgrades, or even transferring the conversation to a human agent.

This will show a potential customer that your brand is concerned about the needs and desires of its audience and will proactively take steps to elevate their purchase experience.

Seamless handover to human agents

Chatbots may often encounter frustrated customers who’re visiting the website looking for support contact details, FAQs or more insights into the products. However, they may not be able to identify the negative emotions of a visitor right off the bat, even with their sentiment analysis capabilities.

During such circumstances, a well-defined fallback can assist in transferring the conversation to the appropriate human agent. This adds another dimension to their utility — that of emotionally intelligent digital assistants.

There are usually these two cases when a chatbot can be programmed to handovers the call to a human agent:

• When the chatbot gets stuck with a complex query
• When customers want to communicate directly with a human support representative.

Emotionally intelligent chatbots are a great way to ensure only relevant concerns get escalated, thus reducing the workload on human agents. This keeps agent satisfaction levels up and prevents burnout, ultimately enhancing the support a business delivers over voice and other channels.

Respond in different languages

Chatbots can be equipped with the capabilities of responding to customer queries in multiple languages. To integrate new languages, you just need to add some new codes and voice recognition software, and you’ll be able to deliver enhanced customer support.

This feature comes in handy for big companies that operate at a global scale and deal with different types of customers by eliminating language barriers.

Extracts social media conversation insights

Businesses struggle a lot to understand what their target audience thinks about their services.

Customers who are dissatisfied with a product or service frequently express their dissatisfaction on social media. Even happy customers use social channels to share their happiness with the rest of the world.

You can use AI-powered conversational bots to interact with your audience over social media to provide recommendations, seek feedback or resolve their queries.

Once you know what your customers expect from your brand, you can modify your offerings and strategies, ultimately boosting your sales.

Since these chatbots are empowered with sentiment analysis and can respond empathetically, the conversation will not sound robotic to your audience. As a result, our business will be able to build stronger customer relationships.

Assists in product recommendation strategy

Upselling and reselling products is not only a great way to keep the sales going but also to retain your existing clientele.

However, your clients are only going to come back to you if you’re able to fulfil their expectations and maybe even take things up a notch with your service delivery.

Chatbot sentiment analysis can be used to determine if your customers are happy with your offerings, not just in terms of your products and services but also the experience you deliver.

If the visitor seems to be happy while interacting with your chatbot, the tool can go ahead and recommend more products and services to them. Conversely, if the visitor appears to be angry, the chatbot can be programmed to avoid any sales pitches and instead route the customer to a human agent.

This will prevent any further aggravations and offer you a greater chance of appeasing them.

Filter out non-potential customers

Many businesses face difficulty in filtering out non-potential customers from a massive list of user bases. Not all customers are valuable; some would be beneficial, while others you may wish to avoid for various reasons.

The latter includes prospects who sound casual about a purchase.

AI-powered chatbots can identify visitor intent by picking up on the tone and words they use during the conversation and filter them into a category accordingly.

This prevents businesses from investing their time, effort and money into leads who may never convert. Instead, they can divert their resources to quality prospects or even towards client retention.

Keyword Mapping

Customers tend to use keywords throughout their interactions with a chatbot. The sentiment analysis tool can be programmed to identify the various words that accompany their sentiments about the brand.

Once this data is collected and segmented by the chatbot, businesses can categorise and create a keyword map from the words that the customers generally use with positive or negative sentiments.

Let’s say, a company’s chatbot interacts with a frustrated buyer who uses the word “CRM” in an angry tone. The chatbot’s sentiment analysis can help the business identify the CRM system as a pain point and help them fix issues before they snowball into a big problem.

Limitations of chatbot sentiment analysis

Sentiment analysis can certainly make bots smarter and significantly boost their skills to ensure greater customer satisfaction. However, the tool comes with its own limitations, so the adoption of conversational AI is yet to reach its full potential.

The following are some limitations of chatbot sentiment analysis:

• Sarcastic text: The use of sarcasm in texts can mislead sentiment analysis algorithms since chatbots struggle to understand phrases that typically have negative connotations yet employ favourable terms
• Word ambiguity: Since words can have multiple meanings based on the context or sentence, bots employing sentiment analysis may struggle to determine what the customer is trying to communicate
• Multipolarity in sentences: A sentence with multipolarity is difficult to understand and recognise for chatbots equipped with the sentiment analysis feature
• Lack of empathy: Chatbots empowered with sentiment analysis can be pretty advanced but they can never empathise with a customer as well as a human agent can

Wrapping it up

Artificial intelligence and sentiment analysis together can power highly sophisticated chatbots that can deliver value to your support staff. Safe to say, you can place your confidence in AI-powered chatbots to improve your customer’s experience and satisfaction level.

Thus, you must invest in chatbots driven by ML and NLP to provide your company with a competitive advantage and offer enhanced customer service.