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Use web scraping to build a data-driven product

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By the one and only

Product data, whether from e-commerce sites, auto listings, or product reviews, offers a treasure trove of insights that can give your business an immense competitive edge in your market. Its intelligent consumption can revolutionize day-to-day business across every function, unleashing new potential for not only business intelligence teams, but also their counterparts

in marketing, sales, and management that rely on accurate data to make mission-critical business decisions.

In this guide, we’ll give you a sneak peek into five of the most common and impactful use cases companies use product data for in their businesses, which will hopefully, inspire you to see the new ways your business can gain a competitive edge in your market.

  • Dynamic pricing and revenue optimization
  • Competitor monitoring
  • Product trend monitoring
  • Investment decision making
  • Brand and MAP compliance

Dynamic price monitoring and revenue optimization

To make profitable pricing decisions, having access to a timely, reliable source of high-quality data is crucial. Large scale product monitoring using web scraped data gives companies the ability to have a finger on the pulse of the entire market, facilitating dynamic pricing, revenue optimization and ensuring they’re always one step ahead of their competitor’s product positioning strategies.

By scraping pricing and product data, business intelligence teams are empowered to confidently position their products and services and make more intelligent pricing decisions.

Competitor monitoring

Using online product data to track your competitors is as old as the internet itself. However, due to the scale and scope of the data available on the web, competitor analysis becomes even more effective when web scraped product data is incorporated into the process.

Advancements in big data and machine learning technologies mean that companies can build sophisticated competitor monitoring capabilities at a fraction of the cost they could previously. Leading to a huge demand for publically available data about their competitors, especially product data. When used effectively web scraped product data can reveal insights into a competitor's product positioning, future product launches, sales and promotion strategies, and customer sentiment towards their products. 

Product trend monitoring

Whether it’s a long, slow shift or a trend cycle as rapid as those in fashion or technology, those who can see the farthest ahead - and most accurately - into future trends emerge on top. The scale and multidimensional aspect of online product data make it perfect for product trend monitoring, and once integrated into product management systems, product data enables companies to see farther, predict more accurately, and drive long term revenue growth.

Developing in-house product trend monitoring capabilities gives companies the ability to consistently and quickly launch and market successful products while mitigating the risk. Online retailers can even use machine learning and web scraped product images to carefully calibrate the way they describe and advertise products, especially powerful as an e-commerce solution to capture market share, boost search rankings, and enhance profitability.

Investment decision making

Hedge funds and account managers are increasingly incorporating alternative data streams into their decision making processes, hoping to gain an information edge over the market and generate alpha. As a result, the demand for product data continues to surge, with a majority of institutional investors increasing the amount of web scraped data they consume. Given its predictive utility, it’s not hard to see why product data is of huge interest. 

Scraping YoY category share trends from online retailers produce powerful predictive indicators of revenue momentum and stock performance, while aggregate pricing histories can allude to problems with sell-through trends and inventory. Furthermore, search data related to the frequency and timing of online searches for a product or company provides strong signals for product sales, especially when observed against competitor averages.

Brand and MAP compliance

The world’s most renowned companies face an uphill battle in ensuring their branding and messaging is consistent at every point of customer contact. A brand’s credibility - and its MAP (Minimum Advertised Price) policy - are integral to survival. Continuously scraping your own product data is not only the fastest and most effective way to maintain compliance across resellers and retailers but perhaps one of the only methods of truly enforcing consistent compliance in real-time. Channel partners can no longer get away with flash sales, designed to dip beneath MAP/MRP agreements, and expect to get away with it.

Web scraped product data enables intelligent MAP monitoring systems to be implemented into product management systems, enabling rapid identification of violations. These systems can compare prices against agreements and immediately notify legal teams of breaches, while simultaneously aggregating evidence and suggesting a course of action. By acting fast to discover MAP violations, businesses availing of this data solution reduce overall risk and protect revenue.

From marketing and sales teams to product development and executive leadership, product data enables functions to realize their fullest potential and endows business with a competitive edge in today’s ever-globalizing, ever-digital market. 

As the market continues to grow, the amount of product data generated grows with it, opening new opportunities for businesses to improve their processes and improve decision making. Therefore, it’s critical for today’s businesses to act as quickly as possible to integrate product data into their product management systems, as otherwise hidden insights can greatly inform directional strategy and ensure company competitivity.

Learn more about web scraping for product data

Here at Zyte (formerly Scrapinghub), we have been in the web scraping industry for 12 years. We have helped extract web data for more than 1,000 clients ranging from Government agencies and Fortune 100 companies to early-stage startups and individuals. During this time we gained a tremendous amount of experience and expertise in web data extraction. 

Here are some of our best resources if you want to deepen your web scraping knowledge:

Written by Colm Kenny