Why is Outsourcing Web Scraping Services Ideal for Data Collection?

The volume of data generated online is immense — 149 zettabytes in 2024, projected to reach 394 zettabytes in the next five years. But are companies able to effectively collect and utilize this data? The answer is no! Most businesses are not able to access it because they are not proficient in web scraping, a process that involves extracting publicly available online data and converting it into a structured format for key tasks such as:

• Competitive Pricing Analysis
• Market Trend Identification
• Lead Generation
• Sentiment Analysis

But why does it happen? In-house web scraping teams struggle with data accuracy, scalability, and compliance due to frequent website changes, anti-scraping barriers, and a lack of advanced infrastructure. Outsourcing web scraping services solves these challenges for reliable data extraction. If you are wondering how let’s dive in and read more about it! 

Two Ways to Implement Web Scraping for Your Business

Web scraping can be performed using two approaches, i.e., automation and manual. Both approaches have their own advantages and disadvantages that you must know to make the right call:

1. Automation

Automation tools, APIs, and custom scripts enable businesses to extract and structure information efficiently at a scale for diverse use cases.

Automation tools & custom scripts enable targeted scraping, ensuring specific data points are captured accurately. However, frequent website updates or anti-scraping measures require ongoing script modifications, making its maintenance time-consuming.

On the other hand, APIs provide a structured and legally safer way to access data, reducing compliance risks. However, not all websites offer/support APIs for data extraction and those that do often have rate limits or require paid access.

Whether you choose custom scripts, automated tools, or APIs, compliance with frameworks like GDPR or CCPA and human oversight is required for secure & responsible data handling. 

2. Manual Techniques

It involves copying and pasting data manually from various web sources into structured formats like spreadsheets. Manual web scraping is ideal for small-scale, niche-specific data extraction where precision matters, such as gathering competitor pricing insights, industry trends, or localized market research. 

It offers greater control over data selection, ensuring accuracy in cases where automated tools struggle with CAPTCHA restrictions, dynamic websites, or complex data structures. However, it becomes challenging when scalability and process efficiency come into play. Extracting large volumes of data manually is time-consuming, error-prone, and resource-intensive.

The advantages and limitations of each approach are summarized here to help you make the right choice:

Ideal Approach- Utilize Both Manual Techniques and Automation 

To maintain both accuracy and efficiency in the web scraping process, it is better to leverage both automated and manual techniques. Custom scripts, tools, and APIs can be used to scrape data quickly from the relevant sources, and then manual data checks can be conducted to keep the scraped data free from errors, inconsistencies, and duplicates. For that, businesses can either hire an in-house team of web scraping experts or partner with reliable outsourcing firms. To choose between these two approaches, read on!

Why In-House Web Scraping Falls Short and How Outsourcing Fixes It?

Building an in-house web scraping team can have challenges in terms of scalability, data accuracy, and compliance. Let’s read in detail about these challenges and learn how outsourcing can solve them:

1. Handling Frequent Website Structure Changes

Many websites frequently change their website structure by making HTML alterations and adding random elements to the page. They also implement anti-scraping measures in the form of CAPTCHAs and IP blocking to prevent bots from accessing and scraping the website. In-house teams have to deal with the additional task of monitoring these changes continuously and updating/modifying their scraping scripts to bypass anti-scraping measures. All of this requires more technical expertise than they might have. 

How outsourcing helps: Reliable web scraping service providers use custom scripts, adaptive parsing techniques, proxy servers, and domain expertise to solve the challenges related to CAPTCHAs and IP blocking. They also have a team to monitor websites’ structure updates in real time, ensuring uninterrupted data extraction while staying compliant with legal frameworks. 

2. Lack of Advanced Infrastructure for Real-Time Data Access

Many businesses require real-time data like weather updates, changing stock prices, and live scores for their analysis. To scrape this large amount of data, enterprises need distributed computing power that can handle simultaneous requests without latency or downtime. However, investing in such infrastructure is not practical for many businesses due to budget constraints. 

How outsourcing helps: Service providers have dedicated cloud-based infrastructure to scrape real-time data efficiently on a large scale. These solutions allow for faster processing speeds, high availability, and real-time scalability. Service providers also use rotating proxy servers to distribute requests across multiple IPs and deploy end-to-end automated workflows for continuous data extraction. These pipelines ensure real-time data updates, deduplication, and error handling, eliminating the necessity for manual intervention.

3. Ethical and Legal Web Scraping Challenges

Companies generally need to follow the ethical code of web scraping and navigate data privacy laws like GDPR, CCPA, and HIPAA, ensuring they don’t collect personal or sensitive data without consent. In-house teams follow aggressive scraping techniques to meet delivery deadlines, which risks damaging relationships with data sources.

Moreover, their lack of legal oversight increases the risk of non-compliance. Scraping against a site’s ToS can lead to legal action, IP bans, or reputational damage if not handled carefully.

How outsourcing helps: Data collection service providers generally implement rate limiting and adaptive crawling techniques to prevent site disruption. Moreover, their teams stay up-to-date with data privacy regulations to ensure compliance.

4. High Operational Costs & Resource Drain

Setting up and maintaining an in-house web scraping team requires hiring specialized developers, maintaining servers, and handling data storage, all of which demand significant time and budget that companies might find hard to allocate, especially when they have a resource crunch. 

How outsourcing helps: Outsourcing to reliable web scraping service providers eliminates these overhead costs, offering a pay-as-you-go model that scales with business needs.

5. Dealing With Data Accuracy and Quality Control

To make the scraped raw data usable for diverse applications, it is critical to first check it for inconsistencies and errors. In-house teams usually struggle with data cleansing and validation processes due to a lack of data governance frameworks or automated tools. It leads to inaccurate, duplicate, or incomplete data. Without automation or AI-driven quality control processes, they end up manually cleaning and verifying data, slowing down their operational efficiency.

Solution: Web scraping providers leverage automated tools for error detection and data cleansing. They employ a human-in-the-loop approach to check and validate scraped data, ensuring that clients get high-quality, structured data. This saves businesses from investing and maintaining specialized tools.

Due to the above-stated benefits of web scraping services, the data collection market is expected to grow at a CAGR of 14% from 2023 to 2030. Businesses can now focus on leveraging insights for growth rather than dealing with the technical complexities of data extraction.

How to Choose a Reliable Web Scraping Service Provider?

With so many web scraping providers available in the market, how do you make the right choice? Here are some factors to consider:

Expertise and Track Record: Look for providers that have prior experience in providing web scraping and data cleansing services. You can check their reviews on platforms like Clutch and GoodFirms to understand if they have relevant experience within your industry. 

Scalability: Data demand for businesses keeps on changing as they are required to scrape real-time data, handle data volume fluctuations, and adapt to evolving website structures. A service provider must be able to keep up with your evolving and growing data collection needs without compromising process efficiency and accuracy.

Compliance Knowledge: Check if they adhere to GDPR, CCPA, and website terms of service to ensure secure and responsible handling of data. They should also follow ethical data collection practices to help avoid legal risks and ensure long-term viability.

Data Quality Assurance: Check if they implement multi-level data validation, deduplication, and error-checking mechanisms. Clean, structured, and accurate data ensures better business insights and decision-making.

Custom Solutions: Look for service providers that offer tailored data collection solutions to individual business needs. They must be able to deliver data in your preferred formats. Also, check if they prioritize the humans-in-the-loop (HITL) approach to make sure that high-quality data is retrieved. 

Addressing Common Concerns About Outsourcing

Outsourcing web scraping offers efficiency and scalability, but businesses often have concerns about data security, vendor reliability, and long-term dependency. Addressing these factors ensures a smooth outsourcing experience.

1. Data Security

For businesses, one of the biggest concerns with outsourcing web scraping is the confidentiality and protection of sensitive data. To mitigate this risk, businesses should:

• Partner with certified providers who comply with ISO 27001, HIPAA, GDPR, and CCPA regulations.
• Ensure that service providers follow encryption protocols for data transmission and storage.
• Sign NDAs and data protection agreements to prevent unauthorized access or misuse.

2. Vendor Reliability and Transparency

Trust is critical when outsourcing web scraping. Not all web scraping providers maintain consistent data quality and ethical scraping practices. Businesses can:

• Opt for trial projects before committing long-term to any vendor.
• Request vendors to provide real-time monitoring and transparent reporting.
• Ensure the vendor provides regular progress updates, quality control measures, and data validation processes.

3. Long-Term Dependency

Companies worry about becoming overly dependent on third-party providers. To address this:

• Select vendors that offer customizable solutions rather than rigid contracts.
• Maintain partial in-house teams for critical tasks while outsourcing high-volume scraping.
• Ensure data ownership clauses in the agreement to retain access and control over collected information.

The Way Forward

Given a choice between outsourcing web scraping and managing it in-house using manual and automated methods, it is advisable to choose the former as it provides businesses with specialized professionals and advanced tools that ensure faster and more accurate data collection. As a result, companies can focus on core operations and strategic growth while relying on experts for reliable data collection solutions.