Pricing intelligence involves data acquisition and processing for optimizing dynamic pricing strategies that will set you apart from competitors positively and give you increased profit. It’s a critical part of many businesses and dynamic pricing is one of the strategies that is used to implement pricing intelligence.
Dynamic pricing also known as real time pricing allows businesses to provide flexible prices for their products and services. In this process, a product is valued based on the market conditions at that point in time.
Benefits of Dynamic Pricing
- It brings about faster response to changes in demand for a product or service
- It provides better control on pricing strategy
- Increases generated revenue
- The price changes from dynamic pricing also takes into consideration the customer’s price perception
Factors That Affect Product Valuation
In dynamic pricing, external and internal factors that are related to the valuation of a product or service are tracked. The internal factors include:
- Production cost
- Shipping cost
It’s more difficult to track the external factors as they vary with changes in season, holidays, competition, consumer behavior, and a lot more. For dynamic pricing to be efficient, there has to be an accurate and effective process involved in data extraction and parsing.
Since data is dynamic, it can be difficult to acquire it accurately. To allow for continuous scraping and scanning process of a web page, data extraction is divided into different processes:
- Use of proxies
- Building data extraction scripts
- Building a scraping path
- Parse extracted data
- Store parsed data
Each step has its challenges but they are not all difficult to bypass. Extracting pricing data on its own isn’t a difficult task, but the problem arises when the websites prevent the process from proceeding.
Strategies that eCommerce Businesses Can Use for Pricing Optimization
1. Use Dynamic Pricing for Your Products
Dynamic pricing allows your product price to be flexible and subject to change when there are changes to competitor prices, demand, and also supply. Since customers are more likely to patronize the retail store whose price is the cheapest, you need to constantly change your pricing to the most competitive one.
2. Competitor Price Analysis
This allows you know where you stand in terms of pricing against your competitors. You first of all define who our competitors are and you can do this with tools such as SEMrush. Then you track the prices of the established competitors and analyze extracted data.
3. Take Note of The Willingness To Pay at A Fixed Price
When you arrive at a price for your product, you also need to evaluate the customer’s willingness to pay for that product at that price. This is mostly valuable for new businesses who are trying to break into the market.
In measuring willingness to pay, judge your customers based on criteria like their location, their employment status, age, income, purpose, volume of purchase, etc.
The Process of Pricing Data Extraction
To optimize dynamic pricing, real-time data in all accuracy is required. There are some ways in which you can get such fresh data for dynamic pricing strategies, and implementing a pricing data extraction is one of them.
Data extraction is a general term for the following processes:
- Developing and using web scraping scripts
- Using headless browsers and their automation
- Parsing extracted data
- Store parsed data
It's relatively easy to build a pricing data acquisition tool, as long as your team is made of those with experience in programming.
Several programming languages have easily accessible libraries these days and it makes it easier to build data extraction scripts and to parse the extracted data. Some open-source tools like Beautiful Soup serve as good starters for some projects.
It is challenging to maintain a dynamic flow of pricing data as most websites are not open to giving off large chunks of data to a bot using python script. And so they have built-in algorithms to help with the detection of bot activity.
Your success in avoiding anti-bot detection algorithms depends on two factors; understanding how the websites work to detect bots and IP rotation.
Avoid getting your IPs Blocked
There are two ways to scrape the web for pricing data: by the use of proxies, or the use of web scraping tools like Real-Time Crawler.
With proxies, web scrapers can use different IPs which can be rotated to make it harder to be detected as a bot. The frequency of IP change, work volume, and other parameters are not fixed and depend on the task.
Web scraping goes beyond having a large pool of IPs. It also requires a large degree of customization:
- City and country-level targeting
- Sticky ports
- Backconnect entries
- Session control
It can be difficult to manage proxies without having a dedicated developer team. And so many people outsource their data acquisition tasks as it's more time and cost-efficient.
RTC is an efficient way to extract data and handles tasks such as data extraction, proxy management, and other tasks that will take up time. This leaves the analysis and data management to the companies to use as they deem fit.
Real-Time Crawler also makes it a less daunting task to extract data from high-security websites without asking for an increase in resources. Large eCommerce websites and search engines are particularly difficult to scrape because they have advanced anti-bot algorithms.
Your data scraping script and the team would most likely have to create workarounds after a series of trials and errors, slowing your project down. It also leads to blocked IP addresses, unreliable data, and increased expenditure.
Real-time crawler makes data acquisition easy because of the following:
- They have over time perfected their method which gives great success each time
- It’s highly customizable for any scraping plan and it’s also scalable
- You get accurate pricing data based on location
- It’s easy to implement RTC into any project using their API
- Extracted data is fully parsed in JSON format
A real-time crawler is a go-to service for businesses that are not so much interested in the development process of web scraping as they are in the data.
It can easily scrape large eCommerce sites and search engines too, making it the right tool for major projects involving hard target sites.
With a Real-time crawler, you can get parsed data in two ways; either through Callback or Realtime with callback, both single and batch queries can be sent.
Larger queries will take longer but you can check their status by sending a GET request. You can also get a message once the task has been completed if a callback URL is provided. If you choose the Real-time option, you will get the data on an open connection.
All results are stored in the database by default, but you can change this easily by providing your preferred cloud storage.