Optimizing Dynamic Pricing for E-commerce

Pricing intelligence is the process of acquiring and processing data in order to optimize pricing strategies and drive growth in profits. It is quickly becoming a critical part of any consumer-facing  business as dynamic pricing is an increasingly important process in most sectors. While dynamic pricing is just one way to implement strategies developed using pricing intelligence, it is the most common one.

Dynamic pricing requires companies to track many external and internal factors related to the valuation of a product or service. Internal factors include:

• Stock 

• Production costs 

• Shipping costs

Meanwhile, external aspects are harder to track as they might vary due to time (seasonal weather changes, holidays, etc.), consumer behavior (such as trends and brand loyalty), competition and many other factors. Yet, most of all, efficient dynamic pricing requires an accurate and effective process of data crawling and parsing.

Acquiring accurate data can be challenging due to the constantly changing nature of consumer information. Data extraction can be divided into several different processes that allow for the continuous scanning and scraping of the Internet. These processes are: 

• Building a scraping path 

• Creating data extraction scripts

• Proxy management 

• Data storage 

• Data parsing

Each of these steps brings their own challenges, although, implementing a pricing data extraction process isn’t difficult in itself. Issues often arise whenever websites start fighting back against data scraping.

Implementing the pricing data extraction process

In order to apply dynamic pricing, accurate and real-time data is required. Implementing a pricing data extraction process is one of the few ways to continuously acquire such data as only fresh information can be used for dynamic pricing strategies.

Data Acquisition

Data acquisition is an umbrella term for a 4-step process:

1. Developing data extraction scripts and implementing them

2. Using (headless) browsers and their automation

3. Data parsing

4. Data storage

Building a pricing data acquisition tool is generally not too difficult for teams with dedicated and experienced developers. Nowadays at least several languages have easily accessible libraries that make building data extraction scripts and parsing acquired information significantly easier. Additionally, open source tools (e.g. Beautiful Soup) can serve as good starting grounds for some projects.

On the other hand, maintaining a constant flow of pricing data is challenging. Most website owners aren’t too keen to give large swaths of data to anyone with a Python script. As such, most data extraction targets (especially ones that are critical to pricing intelligence) have built algorithms to detect bot-like activity.

Avoiding anti-bot detection algorithms relies on two key factors – understanding how websites detect bot activity and consistently rotating IP addresses through proxies.

Avoiding blocked IPs

There are two ways to consistently scrape the web for pricing intelligence – using residential proxies or using a web scraping solution such as E-commerce Scraper API (part of Web Scraper API).

Residential proxies allow web scrapers to acquire IP addresses of physical devices which makes detection significantly harder. These proxies need to be consistently changed in order to avoid bot detection algorithms. Exact details on IP change frequency, work volume etc will depend on the scraping target. 

Efficient web scraping requires not only a large pool of residential proxies in the world but also a large degree of customization:

• Backconnect entries 

• City and country-level targeting

• Session control 

• Sticky ports.

Managing proxies without a dedicated developer team is a daunting task, therefore many Oxylabs clients choose to outsource their data acquisition pipeline. After all, it is often significantly more time and cost efficient. Our data collection tool is created for those looking to focus mainly on data analysis and developing dynamic pricing strategies.

Out-of-the-box solutions like Web Scraper API bring many benefits to those looking for a reliable way to extract data. Proxy management, data extraction script development and other resource-intensive tasks are done on the side of the provider, allowing companies to focus making use of the data. 

Additionally, tools like Web Scraper API can extract data from challenging targets without the requiring increased resource allocation. Scraping large e-commerce websites or some search engines can require additional development time as these targets often create sophisticated anti-bot algorithms. In-house solutions would have to create workarounds through trial and error which means inevitable slowdowns, blocked IP addresses and an unreliable flow of pricing data.

Tools like Web Scraper API make data acquisition easy because:

• High data acquisition success rate

• Implementing Web Scraper API into any project is easy

• Highly scalable and customizable

• Receive fully parsed data (in JSON format)

• Accurate geo-location based pricing data

• Updates are managed on our side

Oxylabs’ Web Scraper API strength lies in its ability to be tailored to almost any business case. The API can easily scrape the largest e-commerce and search engine targets without any hiccups. It can be easily implemented in place of proxies (through Proxy Endpoint) if a scraping solution has already been built.

Web Scraper API in detail

Our Web Scraper API is an out-of-the-box solution for businesses looking to cut through the development process and move straight to data analysis. It is well suited for scraping and acquiring data from search engines and large e-commerce websites.

There are two ways to receive parsed data from our Web Scraper API tool – Callback or Realtime. Callback allows for both single and batch queries to be sent. Larger queries might take some time and their job status can be checked by sending a GET request. For some tasks (if a callback url is provided) we will send you a message automatically once the task has been completed.

On the other hand, the Realtime option is exactly what it says on the tin – we send you the data on an open connection (timeouts are 100 seconds). Ensure that timeout times align as sending data over might take some time.

By default, all Web Scraper API’s results are stored in our databases which means extra queries. This setting can easily be changed by providing your own cloud storage.

Web Scraper API is an exceptional tool for pricing intelligence as it covers the entire data acquisition and parsing pipeline with 24/7 system monitoring. Resources can be heavily geared towards providing dynamic pricing solutions to clients.

Both residential proxies and Web Scraper API work great for data acquisition: