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The success of your business is dependent on your ability to translate insights from customer sentiment analysis into result-oriented actions. 

With the rise of online reviews, social media conversations, and feedback channels, businesses like yours are turning to AI tools to glean valuable insights into customer emotions and opinions. From managing brand reputation to crafting personalized marketing campaigns, AI-powered sentiment analysis tools are revolutionizing the way companies operate and interact with their customers.

In this article, we will examine how big brands hypothetically use AI for understanding consumer sentiment analysis. You will also learn about some of the major AI tools helping businesses understand customers more effectively.

Understanding Customer Sentiment Analysis


Customer sentiment analysis, often referred to as opinion mining, is the use of artificial intelligence to decipher the emotional tone of customers. While the popular use case is analyzing textual data or transcript, martech has evolved to a level where multimodal AI tools like Insight7 can now analyze video, audio, and other recordings. 

By analyzing customer feedback, businesses can uncover valuable insights into customer preferences, satisfaction levels, and pain points. It is these insights that enable them to make informed decisions and supercharge the overall customer experience. 

Popular Use Cases of Customer Sentiment Analysis with AI

1. Reputation Management

Brand Example: Starbucks

Starbucks utilizes sentiment analysis to monitor public sentiment surrounding its brand. By analyzing social media conversations and online reviews, Starbucks can proactively address any negative feedback and capitalize on positive sentiments to strengthen its brand reputation. This allows Starbucks to maintain a positive brand image and foster customer loyalty.

Another popular AI use case for Starbucks is their Deep Brew AI Program which went live in 2019. Starbuck uses this program to automate and create personalized experiences for their customers. In 2021 alone, they spent $618 million on their digital efforts such as machine learning, data analytics, and IoT technologies. 

In essence, your business can also leverage customer sentiment tools such as Brandwatch, Hootsuite, and Hubspot to collate customer sentiment, while AI tools like Insight7 helps you analyze these files to better manage your brand reputation.

2. Product Analysis

Brand Example: Samsung

Samsung leverages AI-driven sentiment analysis tools to gather insights into customer feedback on its products. Through the analysis of product reviews and customer surveys, Samsung can identify areas for improvement and innovation, ensuring that its products meet customer expectations and preferences. This enables Samsung to stay ahead of the competition and drive product innovation.

While that is obviously less talked about use cases, Samsung has been positioning itself as a big player in the artificial intelligence industry. In 2018, Samsung hosted the Artificial Intelligence Summit; considering the new release of their Galaxy AI and their 2017 Bixby AI, it is safe to assume Samsung’s AI use cases go beyond product analysis.

2. Voice of Customer Analysis

Brand Example: Nike

There are few brands that have consistently been in sync with their customers like Nike. The sportswear brands understand the importance of listening to its customers’ voices to stay competitive. 

This is why they launched the Nike Fit tool to help customers determine their size and avoid ordering the wrong shoe size. This particular initiative was informed by a research carried out by Nike, which revealed 60% of people wear the wrong shoe size. They have also ventured into other applications of AI to understand customer needs better and improve customer experience.

By leveraging AI-powered sentiment analysis, Nike can analyze customer feedback across various channels and segments, gaining valuable insights into customer preferences and needs. This allows Nike to tailor its products and marketing strategies to better resonate with its target audience.

For your brand, you can use tools such as Monkey or the popular Insight7 to analyze and understand how your customers perceive your brand.

4. Market Research Competitor Analysis

Brand Example: Walmart

Walmart utilizes AI-driven sentiment analysis to gain insights into market trends and competitor perceptions. 

While Walmart obviously holds a large percentage of the US market share, it can still use AI market research tools to understand consumer sentiment towards its products as well as those of its competitors. This allows Walmart to identify opportunities for differentiation and innovation, ensuring its continued success in the market.

Other ways Walmart is using AI to optimize its user experience includes the conversational AI, Shop with Friends feature, and a generative AI feature that lets users search for product use cases and get accurate results.

5. Customer Support Feedback Analysis

Brand Example: Delta Airlines

Delta Airlines employs AI-powered sentiment analysis to analyze customer feedback and improve its support services. 

By proactively knowing and addressing customer issues, Delta Air Lines enhances customer satisfaction and loyalty, ultimately driving business growth and success. This enables Delta Airlines to maintain its reputation as a customer-centric airline.

Other AI usage for Delta Airlines: 2023 was the AI climax for the people-friendly airline. The company incorporated AI into its customer service and pricing, ultimately improving its overall customer experience. 

6. Real-Time Customer Insights

Brand Example: Meta

You probably live under the rock if you’ve not heard about Facebook in the data and consumer insight conversation. 

Facebook leverages AI-driven sentiment analysis to gather real-time insights into customer sentiment and preferences. Facebook identifies  emerging trends and customer preferences by analyzing customer feedback. This enables Meta to tailor its content and recommendations to better meet customer needs. 

Customer sentiment analysis provides Facebook  with actionable insights to stay ahead of the competition and maintain its position as a market leader in social media.

7. Product Development Optimization

Brand Example: LG Electronics

LG Electronics utilizes AI-driven sentiment analysis to optimize its product development processes. 

Analyzing customer feedback and reviews helps LG Electronics to identify areas for product improvement and innovation, ensuring that its products meet customer expectations and preferences. This feedback has been the reason LG Electronics continues to deliver high-quality products that resonate with its target audience.

As for other AI cases, just like Starbucks, LG has an AI incorporated in LG TVs that provide personalized experience for users.

8. Personalized Marketing Campaigns

Brand Example: Coca-Cola

Coca-Cola employs AI-powered sentiment analysis to develop personalized marketing campaigns. 

Customer sentiment and preference analysis helps Coca-Cola can tailor its marketing messages and promotions to better resonate with its target audience. Last year, Coca-Cola used insights generated and AI to create their latest flavor, the Y3000 Zero Sugar

Over the years, sentiment analysis has enabled Coca-Cola to drive customer engagement and loyalty, ultimately leading to increased sales and revenue.

9. Predictive Analytics

Brand Example: General Motors

General Motors utilizes AI-driven sentiment analysis to predict future trends and customer behavior. 

Through historical sentiment data analysis, General Motors identifies patterns and trends, allowing it to anticipate customer needs and preferences. A recent case study of this was in 2023, when General Motor partnered with Google for Onstar emergency feature.

Overall, sentiment analysis has enabled General Motors to make data-driven decisions when it comes to product development, marketing strategies, and business operations.

10. Risk Mitigation

Brand Example: Johnson & Johnson

Johnson & Johnson employs AI-powered sentiment analysis to mitigate risks associated with customer dissatisfaction. 

Johnson & Johnson has been able to identify potential issues and concerns through customer feedback, allowing it to take proactive measures to address them. This enables the drug company to maintain customer trust and loyalty, protecting its brand reputation and market share.

Last year, Johnson & Johnson also jumped on the AI train to advance drug discovery and help patients access treatment faster.

AI Tools for Customer Sentiment Analysis

1. MonkeyLearn

MonkeyLearn offers a user-friendly platform for sentiment analysis powered by AI. It provides pre-built models and customizable tools to analyze customer feedback from various sources, including social media, surveys, and reviews. MonkeyLearn helps businesses gain valuable insights into customer sentiment and preferences, enabling them to make informed decisions and improve customer experiences.


2. Insight7

Insight7 identifies and categorizes sentiments expressed by customers, including positive, negative, or neutral. It provides actionable insights by detecting trends, identifying key themes, and highlighting areas for improvement. Additionally, Insight7 offers customizable dashboards and reports, enabling businesses to track sentiment metrics over time and make data-driven decisions to enhance customer satisfaction, refine marketing strategies, and manage brand reputation effectively.

2. Lexalytics

Lexalytics is an advanced sentiment analysis solution that utilizes AI and machine learning algorithms to analyze text data. Its cloud-based platform allows businesses to analyze customer feedback in real-time and extract actionable insights. With Lexalytics, you can track sentiment trends, identify emerging issues, and optimize their products and services accordingly.

3. RapidMiner

RapidMiner provides a comprehensive platform for sentiment analysis and text mining powered by AI. Its intuitive interface allows businesses to build and deploy sentiment analysis models without requiring extensive coding knowledge. RapidMiner helps you analyze customer feedback from multiple sources and gain valuable insights into customer sentiment and preferences.

4. Clarabridge

Clarabridge offers AI-driven sentiment analysis solutions tailored for customer experience management. Its platform integrates data from various sources, including social media, surveys, and customer interactions, to provide a holistic view of customer sentiment. With Clarabridge, businesses can identify trends, detect anomalies, and take proactive measures to enhance customer satisfaction.

5. Averbis

Averbis offers AI-powered sentiment analysis solutions designed for industries such as healthcare, finance, and retail. Its platform utilizes advanced NLP techniques to analyze unstructured text data and extract meaningful insights. With Averbis, businesses can gain a deep understanding of customer sentiment and preferences, enabling them to make data-driven decisions and drive business growth.

Bonus: 8 Key Benefits Customer Sentiment Analysis

We have seen some of the use cases of customer sentiment analysis and a few AI tools for powering your consumer sentiment analysis projects. Below are some additional benefits of why you need to leverage customer sentiment analysis in 2024.

1. Enhanced Customer Experience:

Customer sentiment analysis allows businesses to gain deep insights into customer emotions, opinions, and preferences. Once you understand how customers feel about your products, services, and overall experiences, you can tailor your offerings to meet customer expectations better. This leads to improved customer satisfaction and loyalty, ultimately driving business growth.

2. Product Improvement:

Through customer sentiment, you can identify areas for product enhancement or innovation. By uncovering patterns in customer feedback, you can pinpoint specific features or aspects of your products that require improvement. It is the most proactive approach to product development ensures that businesses stay aligned with evolving customer needs and preferences.

3. Effective Marketing Strategies:

Customer sentiment analysis provides valuable insights into the effectiveness of marketing campaigns and messaging. Understanding how customers perceive marketing efforts can help you refine your strategies to resonate better with target audiences. The consequence of this is impactful marketing campaigns, higher engagement rates, and increased conversion rates.

4. Brand Reputation Management:

Monitoring customer sentiment enables businesses to manage their brand reputation effectively. In tracking mentions, reviews, and social media conversations, you can identify and address any negative sentiment before it escalates. Proactively managing brand reputation helps safeguard against potential crises and maintains a positive brand image in the eyes of consumers.

5. Competitive Advantage:

Customer sentiment analysis enables businesses to stay ahead of competitors by understanding market trends and consumer preferences. Through insights from sentiment analysis, companies can identify emerging trends, monitor competitor performance, and differentiate their offerings effectively. This proactive approach to market intelligence gives businesses a competitive edge in crowded marketplaces.

6. Risk Mitigation:

By monitoring customer sentiment, businesses can identify and mitigate potential risks proactively. Whether it’s product issues, service disruptions, or negative publicity, sentiment analysis allows companies to detect and address issues before they escalate. This proactive risk management approach minimizes reputational damage and financial losses, ensuring business continuity.

7. Data-Driven Decision Making:

Customer sentiment analysis empowers businesses to make data-driven decisions across various departments. By leveraging insights from sentiment analysis, companies can optimize product development, marketing strategies, customer service initiatives, and more. This data-driven approach ensures that decisions are based on actionable insights rather than assumptions, leading to better outcomes.

8. Improved Customer Engagement:

Understanding customer sentiment enables businesses to engage with their audience more effectively. By responding to customer feedback, addressing concerns, and acknowledging positive experiences, companies can foster a sense of trust and loyalty among customers. This increased engagement leads to stronger customer relationships, higher retention rates, and advocacy for the brand.


Customer sentiment analysis offers businesses a powerful tool for gaining actionable insights into customer emotions and opinions. By leveraging AI-powered tools and solutions, you can analyze customer feedback, identify sentiment trends, and optimize their products and services accordingly. With the right AI tools and technologies, you can enhance customer experiences, drive customer satisfaction, and ultimately achieve business success. 

If you are trying to analyze customer sentiment, check out this free popular AI sentiment analysis tool.