Uncertain events, along with an increasing shift to digital channels, have produced a great need for price discipline and adjustable pricing strategies to help companies serve their customers fairly and efficiently in the e-commerce world. Dynamic pricing is one such pricing structure that has been helping brands capitalize on a changing market while keeping customers happy.
Also called surge pricing or time-based pricing, dynamic pricing is a pricing method that uses technology and techniques, like web scraping, to make adjustments to prices based on varying external factors, including current market demand, supply changes, and competition. This strategy offers several advantages to e-commerce businesses, such as increased revenue, enhanced competitiveness, and improved inventory management.
To help you better understand, we’ll cover types of data used for dynamic pricing and how web scraping facilitates data collection for this pricing structure. But before anything else, let’s have a look at what web scraping is.
Web Scraping: What it’s all about
A type of data scraping, web scraping is a useful technique performed to collect data from online sources through HTML, CSS, and JavaScript code and store it for further processing and analysis.
This method is commonly used to retrieve huge amounts of data for gleaning insights and making business decisions.The collected data helps companies with market research, lead generation, price intelligence, competitive monitoring, SEO analysis, and more.
This process mainly depends on specialized tools or algorithms to go through websites and gather data. In most cases, these software applications follow a series of steps to perform data scraping, which are as follows:
- Request – A scraping tool is used to send an HTTP request to the target platform or website for gaining access and retrieving its content.
- Parse – A parsing tool then parses the content to get the desired elements out of the content, like text, photos, URLs, etc. To learn how to parse XML effectively, one can utilize various programming languages such as Python or Java, employing dedicated libraries like ElementTree or JAXB respectively.
- Display – The extracted content is transformed into a format, such as JSON or CSV, for further processing.
Types of Data used for Dynamic Pricing
Dynamic pricing is a powerful strategy capable of helping online shopping businesses achieve greater profits, improved customer satisfaction, and increased competitiveness. To make this happen, this practice needs some types of data, such as:
- Competitor Prices – Most importantly, dynamic pricing can put competitor prices to use to help brands enhance competitiveness and market share through matching or undercutting prices set by their competitors. They can stay in the lead by adjusting their prices in real-time after market fluctuations.
- Demand Trends – Understanding demand trends is vital for effective dynamic pricing. Sales data, search patterns, and product availability can be used in dynamic pricing to help businesses determine peak demand periods and set prices that align with industry expectations.
- Seasonality – Seasonality refers to predictable fluctuations that occur every year in a business depending on the seasons, such as calendar or commercial seasons. These changes are usually the cause of unknown increases or decreases in sales. Dynamic pricing can leverage data related to seasonal trends to allow E-commerce businesses to adjust prices during peak and off-peak seasons for maximum revenue generation.
- Customer Reviews – Customer reviews provide businesses with an opportunity to know more about their purchasers. Ratings and opinions regarding the product or service give insights into how well a company is performing in the market. Dynamic pricing can use this data to adjust pricing strategies and provide personalized offers and discounts. This helps in providing customers with better prices and higher customer satisfaction and loyalty.
How Web Scraping helps Data Collection?
When it comes to collecting data to adjust pricing strategies, e-commerce web scraping can prove to be a game-changer. The technique automates the collection of the types of data mentioned above from various online sources. It gives a clear picture of the market conditions by retrieving product details, competitor prices, and customer reviews.
These insights allow brands to make data-driven decisions and ensure their pricing strategies stay competitive and align with customer expectations. E-commerce web scraping also enhances competitor analysis by providing companies with meaningful data related to competitor’s strategies.
Brands can discover promotional approaches, product offerings, pricing methods, and other important information that their competitors use to find areas for improvement and change their pricing strategies accordingly.
The process can also be useful in tracking the latest market fluctuations to quickly respond to pricing hikes and maintain a competitive position in the industry.
Final thoughts
To summarize, a number of enterprises, like leading retailers and marketplaces, regularly utilize dynamic pricing to attract more customers and generate revenue. They adjust their prices based on different factors, including consumer demands, competitor prices, and seasons.
To help businesses with this, e-commerce web scraping collects different types of data that are essential to maintain a successful dynamic pricing strategy and stay competitive in the market.
