Finding Business Value in Sentiment Analysis Data
The explosion of social media and the proliferation of mobile devices have created a “perfect storm” of opportunities for customers to express their feelings and attitudes about anything and everything at anytime. This opinion or “sentiment” data, generated through social channels in the form of reviews, chats, shares, likes tweets, etc., often includes comments that can be invaluable for businesses looking to improve products and services, make more informed decisions, and better promote their brands.
The key to business success with sentiment data lies in the ability to mine vast stores of unstructured social data for actionable insights. That’s a formidable task, requiring sophisticated tools such as Natural Language Processing (NLP) to carry out comprehensive examinations of the sentiments of social media users. Fortunately, big data analytics platforms such as cloud-based Hadoop are up to the challenge.
What follows is a look at how businesses can find value in sentiment analysis data.
Enhancing the customer experience
Customer experiences fall into three basic categories, positive, negative or neutral. Through sentiment analysis, companies can detect the tone and temperament of each and every word found in a customer’s social postings and categorize those sentiments as either positive, negative or neutral. Armed with this information, businesses can gain valuable insights into what they are doing right with regard to products, services and customer support—positive sentiments—and what they need to work on—negative sentiments—in order to enhance the overall customer experience.
Gaining competitive advantage
Sentiment analysis not only helps businesses get a read on how they’re doing with their customers, it also gives businesses a better picture of how they stack up against their competitors. For example, a company that has 15 percent negative sentiment may view that as acceptable. But if a direct competitor’s negative sentiment is only 10 percent, that 15 percent negative no longer looks so great. Knowing the sentiments associated with their competitors helps companies evaluate their own performance and look for ways to improve. Sentiment analysis also helps businesses predict consumer trends and develop strategies to capitalize on those trends and gain an edge on the competition.
Gaining Business Intelligence
Sentiment analysis data provides businesses with powerful, insight—rich information about current and future customers—insights that can lead to new business opportunities and possibilities. However, sentiment analysis insights alone aren’t enough. To create actionable strategies businesses will need to integrate business intelligence insights with human insights and other important metrics. Sentiment as a sole metric is not enough.
Revitalizing a brand
Branding is all about perception. And sentiment analysis allows businesses to quantify the perceptions that current and potential customers may have about their products and services, their customer experience, online content, marketing and social campaigns. In short, their overall brand. Access to negative and lukewarm sentiment analysis data helps companies develop more positive and engaging branding and marketing strategies to bring new life and credibility to a stagnant brand.
As good as sentiment analysis is, it will never be as accurate as old fashion human analysis. Unlike the human brain, big data analytics platforms are incapable of picking up on subtleties of delivery, such as body language and sarcastic tone, that give personal comments greater context. Still, as sentiment analysis tools and technologies continue to advance, and the social media explosion continues its present pace, the accuracy gap between machine analysis and human analysis is narrowing dramatically. Going forward, businesses that more fully incorporate sentiment analysis with other proven tools and metrics stand to gain greater business value plus a distinct advantage over their competitors.