Client sentiment analysis

Analyze client sentiment with insights from past discussions

Capabilities & models

Analyze

Palmyra X4

Categories

• Financial services
• Retail & consumer goods
• Support
• Sales

What is customer sentiment analysis?

Customer sentiment refers to how customers feel about your product, service, or brand. It’s typically expressed through support interactions, feedback, reviews, surveys, or social media posts.

Customer sentiment analysis software collects text data from multiple sources and helps you understand it. These tools rely on sentiment analysis algorithms and sentiment classification to detect and categorize customer feedback, whether it’s positive, negative, or neutral.

How generative AI can turn customer sentiment analysis into action

Enterprise companies manage vast customer data across various systems, including CRM platforms, email marketing tools, social media, customer support software, and data warehouses. These systems hold diverse customer information, from purchase history and interaction logs to demographic data and feedback.

Consolidating this data provides a clearer picture of customer sentiment, enabling better decision-making. Customer sentiment analytics also help identify patterns, trends, and expectation shifts, offering valuable insights for strategic planning.

Generative AI excels in analyzing customer sentiment more accurately than traditional tools. While keyword-based methods can be imprecise and miss nuances, generative AI uses advanced techniques to detect sarcasm, tone, and context.

Understand customer expectations

Using AI customer sentiment analysis, you can pinpoint issues such as:

• Frustrations with your products or services
• Negative reactions on social media
• Responses that don’t match your customers’ level of urgency

Improve customer service

Customer sentiment analysis allows you to dive deeply into customer service issues, including problems with wait times or additional training that might be needed. You can also use it to identify customer service representatives who consistently deliver great experiences, even when customers are unhappy.

Customer sentiment analysis across industries

Financial services: Building trust through understanding

AI customer sentiment analysis agents help financial institutions identify customers who might be at risk of churning. These agents continuously analyze support tickets, phone transcripts, and digital communications, automatically flagging early warning signs of dissatisfaction.

Retail: Enhancing the shopping experience

AI sentiment analysis agents help manage this complexity by continuously monitoring and analyzing customer emotions across all channels. Ecommerce retailers deploy sentiment analysis agents to monitor product reviews in real-time, identifying quality issues or shipping problems before they impact a broader customer base.

Consumer packaged goods: Staying connected to consumer preferences

Brand managers deploy sentiment analysis agents to continuously monitor social media conversations about their products, competitors, and industry trends. During product recalls or safety concerns, sentiment analysis agents help CPG companies understand the emotional impact on consumers and automatically adjust communication strategies accordingly.

Better decisions with customer sentiment analysis

Analyzing customer sentiment is often the gulf between collecting data and acting on it. With WRITER, you can connect the client sentiment analysis agent to your company’s data, knowledge, and tools. This allows you to track customer interactions in a repeatable, meaningful way.

Frequently-asked questions

What is customer sentiment analysis?

Customer sentiment analysis is a process of collecting customer interaction data and analyzing it to understand how customers feel based on what they say. During the analysis, customer interactions are assigned a sentiment, such as positive, negative, or neutral.

How can sentiment analysis be used to improve customer experience?

Customer sentiment analysis identifies pain points and factors that improve customer satisfaction. With this information, companies can take action to address customer issues or bolster strategies that are working well.