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Four popular use cases for online public sentiment data

Online public sentiment analysis can transform public emotions into quantitative insight that can be used to drive change. Look at the applications here.

Himanshi Bhatt · Demand Generation Manager

2 min read ·

Four popular use cases for online public sentiment data

Four use cases for online public sentiment data

The manual method of discovery for gauging online public sentiment towards a product, company, or industry is cursory at best, and at worst, may harm your business by providing incorrect or misleading insights.

It is estimated that as much as 80% of the world’s data is not organized. As a result, it is not possible for any human being to even touch the surface of this data. Thankfully, web scraping is a powerful solution providing businesses of every size a useful tool for monitoring online public sentiment.

Simply put, this data can only be properly aggregated to any useful extent if generated in quantities too large for manual input, and web scraping such data has therefore become best-practice across the world’s many public-facing industries.

Sentiment analysis can transform the subjective emotions of the public into quantitative insight that a company or leader can use to drive change. Let's look at some popular use cases for online public sentiment data:

Investment decision making

The market moves quickly, and being even half a step ahead of the competition can be incredibly valuable. If many firms are receiving the same traditional data, investors can differentiate their strategy (and bolster their earnings) by incorporating sentiment data into their decision making. Sentiment data can inform the investment process by predicting future firm fundamentals or stock returns plus event-based sentiment analysis can show savvy investors when to move.

Product monitoring

Any business intelligence strategy is incomplete without an understanding of public sentiment. The way a company’s product or service is portrayed in news articles and reviews directly impacts its bottom line. By scraping qualitative public sentiment data about your product from the web, businesses can integrate this information directly into AI-driven business solutions to produce actionable insights into which products are performing - or underperforming - and why. The uses for sentiment data across the product monitoring are diverse. Here are a few examples: polarity analysis, social media monitoring, aspect-based text analysis, and website variance.

Brand and company monitoring

The adage that any press is good press may be losing its veracity in an era when press and reviews are at our fingertips 24/7. What steps can a company take to protect its reputation in this socially accelerating world? By scraping sentiment data, business intelligence (BI) teams can both capitalize on positive publicity and work to mitigate negative sentiments. A comprehensive BI strategy acknowledges the multi-pronged nature of online sentiment by scraping data from many sources and analyzing many of the factors that comprise sentiment.

Product development

Sentiment analysis based on web scraped data equips product development teams with data-driven insights into the changes customers want to see and the quality of a product’s performance. In this way, sentiment analysis is not just a retrospective but a vital tool in the product creation, planning, and design process. Get insights for every step of development from launching new features to customer feedback from support tickets and monitoring how customers are using your product to help determine new product creation or new features.

Sentiment Analysis, with its useful analysis, opens doors to so many opportunities by providing a solid scientific base to information that was previously mere assumptions. If you are curious about the above applications of sentiment analysis and want to know more, have a look at our whitepaper on ‘Empowering analysis with online public sentiment data’. If you want to know how web scraped news and article data can benefit your business, request a free consultation with our solution architecture team today.

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Himanshi Bhatt

Demand Generation Manager

Himanshi's posts center on business use cases for web data — dynamic pricing, competitive intelligence, customer-review analysis, and travel-industry applications — alongside several years of the "Zyte Developers Community Newsletter" and recaps of the annual Web Data Extraction…

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