Enterprise investment in technology is aligned to increasing efficiency and decreasing costs. In a tough economy ROI is even more scrutinised.
Is social listening a nice to have or must have? Is it a part of the technology lift that can help drive ROI?
Natural Language Processing (NLP) overcomes the limitations of social listening in several ways:
The pain points of social listening are well documented 1) data overload, 2) noise and relevance, 3) inaccurate data, 4) data privacy, 5) reach, 6) time consuming.
1. Improving Data Relevance: NLP algorithms can analyze vast amounts of text data and extract relevant information, such as mentions of a brand, industry trends, and customer opinions. By using NLP, businesses can improve the accuracy and relevance of the data they collect through social listening.
2. Reducing Noise: NLP algorithms can filter out irrelevant or spammy posts, reducing the amount of noise in the data. This makes it easier for businesses to identify meaningful information and insights, and reduces the time required to analyze the data.
3. Sentiment Analysis: NLP algorithms can analyze the tone and emotion behind posts and comments, providing insights into how customers feel about a brand or product. This helps businesses understand the overall sentiment of their customers, and make informed decisions based on this data.
4. Multilingual Support: NLP algorithms can support multiple languages, making it possible for businesses to monitor and analyze social media conversations in different languages.
5. Automation: NLP algorithms can automate the process of social listening, reducing the time and effort required to collect and analyze data. This allows businesses to focus on other important tasks, such as interpreting the data and making informed decisions.
6. Improved Accuracy: NLP algorithms can learn from previous data and adjust their models to become more accurate over time. This helps to reduce the risk of false or misleading insights, and ensures that businesses have access to the most accurate data possible.
In conclusion, NLP can significantly improve the limitations of social listening by providing more accurate and relevant data, reducing noise, and automating the process of data analysis. By integrating NLP algorithms into their social listening tools, businesses can gain a more complete understanding of their customers, competitors, and industry, and make informed decisions based on this data. Whether you are a small business or a large corporation, NLP can help you overcome the limitations of social listening and make the most of this powerful tool.
Talking Medicines apply NLP to classify the patient voice from social media. This technology lift means that the ROI is gained from the accuracy of only listening and analysing sentiment and behaviours of patients who are hard to identify in unstructured data. ROI is also driven from the efficiency and consequential time saving vs current state. It is only by connecting with the data insights on real world patient sentiments and emotions that successful patient centric strategies can be written.
By Jo Halliday, CEO and Founder
