What is sentiment analysis?

The sentiment analysis module uses Artificial Intelligence (ChatGPT 4) to classify text comments regardless of their source. Now we can understand how consumers feel about different business concepts (we call them Topics) and make changes to improve by measuring objectively.

Here's a breakdown of how the sentiment analysis module works:

🔎 Gathering Comments: The process begins by collecting customer comments. These comments can come from various sources:

📌 Topics Selection: to select the topics we want to track to understand consumer perception, we have to think in terms of concepts rather than literal words. For example, if we're about to make business changes to our service offerings, we can track the topics "Price," and RAY will classify comments like "It's not worth what they charge" or "It's too expensive for what they offer" under that topic.

❤️ Sentiment Analysis: through ChatGPT 4, we classify each comment globally and for each topic, taking into account the language and country of the consumer, as expressions and words vary greatly. We classify opinions as:

📈 Sentiment Visualization: The graph shows Positive and Negative comments for the last 6 months, along with the "Net Sentiment," which is simply the difference between the two values. This way, it's easy to see month by month how consumer perception trends change as we make operational changes.

👨‍⚖️ Action Plan: With the report results, companies can make informed decisions on how to address specific areas that may require attention. This allows for more precise operational improvement.

The sentiment analysis module, with the help of artificial intelligence, is an essential tool for understanding customer perception and making data-driven decisions to continuously improve products and services.

This not only increases customer satisfaction but can also drive long-term success for an organization by effectively adapting to the needs and desires of its audience.

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