Why Sentiment Analysis is the Key to Customer Intimacy
Reading Time: 2 minutes
Hidden Value in Unstructured Data
Structured data is easily mined and analyzed, but what about unstructured data? Ninety percent of global data is unstructured, yet most unstructured data is never analyzed. In fact, of all that unstructured data, only one percent of it is ever analyzed.
And it’s not because of a lack of value. Unstructured data holds valuable customer insights. When combined with structured data and other forms of analysis, adding unstructured data to the mix can be a great complement to what you already know about your customers.
Posts and images shared through social media, emails, support call logs, customer chats, and more are all forms of unstructured data too often overlooked. Why? Because it’s easy to stick to what you know. Structured data is more familiar to us, organized in structured ways like columns and rows.
But while unstructured data involves a deeper parsing to extract the semantic meaning, understanding social media interactions, customer calls, and even user reviews, can offer deeper insight into a customer’s wants and needs.
Increasing Customer Intimacy with Sentiment Analysis
The two key aspects of text analytics, sentiment analysis and topic identification, can be used to analyze unstructured data and more deeply understand your customers’ wants and needs. Analyzing unstructured data about customer interactions through sentiment analysis can reveal a lot about customer preferences and how they feel about your company.
Many consumers today say that they consider how aligned a company’s values are with their own personal values when making purchasing decisions. But how do you understand what the values of your consumers are? Sentiment analysis is the key. Whether a small business or a large enterprise, organizations need tools like sentiment analysis to understand the cross-channel customer experience.
Top Use Cases Leveraging Sentiment Analysis
Sentiment analysis contributes to a better understanding of customer intimacy. It’s one component you can use to build a comprehensive, 360-degree view of your current customers and also your potential customers. It’s a way to uncover net new market opportunities and understand the risks involved.
There are a lot of established use cases for sentiment analysis and topic identification for discovering those types of insights, including:
- Demand-Driven Supply: Research and development, dynamic pricing, product launch
- Connected Experience: Market optimization, brand health monitoring, and customer care and support
- Predictive Engagement: Next best action, market basket analysis, and customer lifetime value
Analyzing unstructured data about customer interactions through sentiment analysis can reveal a lot about customer preferences and how they feel about your company. Click To Tweet
Watch this on-demand webinar to go more in-depth about these use cases and see the value of sentiment analysis in a demo using TIBCO Spotfire®’s latest native Python data functions.
And to learn more about how sentiment analysis can help your business improve customer experiences, increase brand loyalty, and even increase revenue, read this guide to getting started.