Data Scraping: Collecting vs Buying

Data scraping is an essential skill for all businesses in 2024. Modern companies and business-minded individuals need information collection and filtering tools to analyze information on the web, including data about competitors, their prices, and marketing strategies.

With data-oriented solutions, we have the power to make accurate decisions. By combining the quality and immense quantity of valuable information into digestible data sets, companies find ways to harness the power of this knowledge, either through innovative decisions, or rapid, automated business adjustments.

Depending on your long-term goals, there are two popular methods for reaching out and acquiring data online. Some companies start collecting information by themselves, while others prefer to buy or order data sets that suit a specific use case.

In this guide we compare both data collection approaches to find the best option for you. Here you will see the advantages and disadvantages of both choices as well as recommended tools if you decide to sake out data yourself. For example, you can buy proxy servers to start your own web scraping tasks and seek out providers with the best proxy prices as well as tools for scalability and flexibility. For serious data scraping procedures, businesses choose long-term deals that give the best value and affordable proxy prices for companies and business-oriented individuals.

Buying Data Sets From Other Parties

Source: leannecalderwood.com

Data set purchases might be a good solution for businesses that are less reliant on constant streams of information. These obtainable knowledge sources give a necessary boost for newly modernised businesses that start their first marketing campaigns and social media management strategies.

Before entering a specific market, some companies place an order for a data set containing products and prices of all competitors. This way, the buyer has an overview of the weakest players, biggest threats, who supplies the most goods and services, plus what are the demands and future predictions of clients.

All things considered, buying data sets is a very limited option, unless you have a long-lasting partnership with continuous information requests. Still, here are the main disadvantages of ready-to-use data:

Buying Data Sets From Other Parties

Depending on the competitiveness of the market, the collected information that the company plans to use for business decisions might become irrelevant in a matter of weeks, days, and even minutes! Also, one order may not paint as broad a picture as expected, leaving knowledge gaps and the need for additional purchases. With no control over data collection tools, you cannot target all desired pages or adjust the information collection strategy on the fly.

No Control Over Quality

Unless your company reaches out to a trustworthy data provider, information purchases leave you no room for control, the quality of data, and other adjustments. Especially for cases where buyers try to save money, there is no way of knowing if collected data will suit your needs unless a reliable supplier provides constant updates. Still, even the best data sets often lack the quality and relevancy of closely orchestrated collection procedures.

Collecting Data With Scraping Bots

Source: charitydigital.org.uk

Running your data collection tasks is the best way to have the most useful information and maintain a steady supply of information. Here are the main reasons modern businesses choose to collect the data themselves.

Control Your Targets

Target control is collecting the most relevant data. Instead of opting out for one big data set, controlling and navigating all the scraping bots gives you all the power. Instead of focusing on irrelevant targets by broadening the horizon, businesses can collect more information from the same concentrated sources, especially if those websites implement frequent changes.

Steady Supply of Data

The biggest advantage of owning your data collection system is ensuring a steady stream of information. With scraping bots firing on all cylinders, businesses in 2024 choose to maintain a real-time supply of data.

This strategy is perfect for analyzing information from competitor retailers and their online shops. These are the targets that contain the most volatile data. Price sensitivity is a common strategy, where competitor businesses use data collection tools to scan the web for prices of similar products.

After obtaining this information, owners can compare the price ranges and make adjustments on their page to emerge as the most attractive option. These sensitive changes also flare up on aggregator websites, where providing the best price for desired products gives your company a large boost in publicity.

Data Scraping Challenges

Source: blog.datahut.co

While tech-savvy at the core of their business model transition easily into web scraping, not all companies have efficient employees to successfully perform these procedures. Here are the main web scraping challenges:

Writing Your Scraper vs Buying Built Tools

Building your scraping bots is a cheaper, more flexible long-term solution that lets you manipulate the process of data extraction. Getting a pre-built tool is faster, but your company will still need trained personnel to adjust parsing tools.

Avoiding Ip Bans

The most valuable web scraping targets know that competitors are out to get them. To counteract the negative effects of automated connection requests, web server owners implement rate limiting and filtering procedures that blacklist IP addresses sending too many connection requests. The best way to avoid bans and continue web scraping without interruptions comes from proxy servers. Businesses in 2024 partner up with proxy providers to protect each scraper with a fake digital identity.

Conclusion

Although ready-to-use data can be a superior option for niche cases, having control over web scraping operations is the best way to collect the most relevant data for all business activities. While collecting data with scraping bots requires some technical skill, the long-term benefits are too great to miss out on full control of information collection opportunities.

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