Top 4 Web Scraping Use Cases in Trend Analysis in 2024
Trend analysis is the practice of detecting patterns in business data that signal a decrease or increase in strategic metrics. It enables data-driven decision making in all industries. Traditionally, trend analysis used to be done with a company’s own data such as sales history or publicly available data such as stock prices. However, with the growing size of web data, businesses have the opportunity to detect real-time changes in the market and enhance their decision making.
In this article, we will explain how web scraping enables trend analysis by automating the extraction of web data, and explore the most common business use cases as well as the benefits of trend analysis.
1. Dynamic pricing
Used widely from e-commerce to airline industry, dynamic pricing enables companies to optimize the price of a product or service online based on competitors’ prices. With web scraping tools, companies can get real time data on how much a product is sold by other websites and maintain their competitiveness.
This use case is so well established that we can confidently say all major ecommerce websites leverage this for their pricing strategy and according to McKinsey, their dynamic pricing strategy helped ecommerce customers grow their sales by 2 to 5 percent.
2. Market research
In their research, Marketing Science Institute defines web scraping as the “gold field” of consumer and marketing research. Scraped web data can reveal how the public opinion about a brand changes over time or detect potential misinformation in real time which may hurt the brand’s publicity.
For example, there are products for tracking brands’ social presence to detect any fraud or misrepresentation. To enable this real time tracking for multiple brands, they use web scraping as a scalable solution.
3. Demand forecasting
For an accurate picture of the demand, online businesses need to track the interest in a product in the wider market too. Companies can use web scraping to track the demand of a product in the entire online market and optimize their supply chain based on real time demand analysis.
Especially with COVID19, companies need to adopt web signals into their demand forecasting a lot more. According to a business solution Boston Consulting Group offers, there is strong correlation between web traffic signals and actual sales in many categories from groceries to luxury goods and amongst other traditional signals in demand analysis, web signals seem to be the leading factor.
4. Financial Investments
Financial markets are dependent on many factors such as political climate, consumer behavior or latest news about companies. As we mentioned in our web scraping for finance guide, web scraping is the top alternative data source currently used by investment firms. With web scraping, venture capitals can detect which startups gain popularity or investment firms can track positive or negative news about the companies they hold the stocks of.
According to a research by Brunswick Consultancy Group, online and social media sources became more central to investment decision-making than past years, including well known platforms as rich information sources such as Wikipedia, Linkedin and YouTube.
Recommended reading
To explore web scraping use cases for different industries, its benefits and challenges read our articles:
- Top 18 Web Scraper / Crawler Applications & Use Cases
- The Ultimate Guide to Web Scraping for Recruiters
- In-Depth Guide to Web Scraping for Machine Learning
If you believe that your business may benefit from a web scraping solution, check our list of web crawlers to find the best vendor for you.
For guidance to choose the right tool, reach out to us:
This article was drafted by former AIMultiple industry analyst Bengüsu Özcan.
Cem has been the principal analyst at AIMultiple since 2017. AIMultiple informs hundreds of thousands of businesses (as per similarWeb) including 60% of Fortune 500 every month.
Cem's work has been cited by leading global publications including Business Insider, Forbes, Washington Post, global firms like Deloitte, HPE, NGOs like World Economic Forum and supranational organizations like European Commission. You can see more reputable companies and media that referenced AIMultiple.
Throughout his career, Cem served as a tech consultant, tech buyer and tech entrepreneur. He advised businesses on their enterprise software, automation, cloud, AI / ML and other technology related decisions at McKinsey & Company and Altman Solon for more than a decade. He also published a McKinsey report on digitalization.
He led technology strategy and procurement of a telco while reporting to the CEO. He has also led commercial growth of deep tech company Hypatos that reached a 7 digit annual recurring revenue and a 9 digit valuation from 0 within 2 years. Cem's work in Hypatos was covered by leading technology publications like TechCrunch and Business Insider.
Cem regularly speaks at international technology conferences. He graduated from Bogazici University as a computer engineer and holds an MBA from Columbia Business School.
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