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Web data extraction possesses tremendous applications in the business world. Some businesses function solely based on data, others use it for business intelligence, competitor analysis, and market research among other countless use cases. While everything is good with data, extracting massive data from the web is still a major roadblock for many companies, more so because they are not going through the optimal route. We decided to give you a detailed overview of different ways by which you can Web Data Extraction. This could help you make the final call while evaluating different options for web data extraction.

Different Routes You Can Take To Web Data

Although different solutions exist for web data extraction, you should opt for the one that’s most suited for your requirement. These are the various options you can go with:

1. Build it in-house

2. DIY web scraping tool

3. vertical-specific solution

4. Data-as-a-Service

Build it in-House

If your company is technically rich, meaning you have a good technical team that can build and maintain a web scraping setup, it makes sense to build a crawler setup in-house. This option is more suitable for medium-sized businesses with simpler requirements when it comes to data. However, building an in-house setup is not the biggest challenge- maintaining it is. Since web crawlers are really fragile and are vulnerable to the changes on target websites, you will have to dedicate time and labor to the maintenance of the in-house crawling setup.

Building your own in-house setup will not be easy if the number of websites you need to crawl is high or the websites aren’t using simple and traditional coding practices. If the target websites use complicated dynamic code, building your in-house setup becomes a bigger hurdle. This can hog your resources, especially if extracting data from the web is not a competency of your business. Scaling up with your in-house crawling setup could also be a challenge as this would require high-end resources, an extensive tech stack, and a dedicated internal team. If your data needs are limited and the target websites simple, you can go ahead with an in-house crawling set up to cover your data needs.


  • Total ownership and control over the process
  • Ideal for simpler requirements


  • Maintenance of crawlers is a headache
  • Increased cost
  • Hiring, training, and managing a team might be hectic
  • Might hog on the company resources
  • Could affect the core focus of the organization
  • Infrastructure is costly

DIY scraping tools

If you don’t want to maintain a technical team that can build an in-house crawling setup and infrastructure, don’t worry. DIY scraping tools are exactly what you need. These tools usually require no technical knowledge as such and can be used by anyone good with the basics. They usually come with a visual interface where you can configure and deploy your web crawlers. The downside, however, is that they are very limited in their capabilities and scale of operation. They are an ideal choice if you are just starting with no budgets for data acquisition. DIY web scraping tools are usually priced very low and some are even free to use.

Maintenance would still be a challenge that you have to face with the DIY tools. As web crawlers are susceptible to becoming useless with minor changes in the target sites, you still have to maintain and adapt the tool from time to time. The good part is that it doesn’t require technically sound labor to handle them. Since the solution is readymade, you will also save the costs associated with building your own infrastructure for scraping.

With DIY tools, you will also be sacrificing the data quality as these tools are not known for providing data in a ready to consume format. You will either have to employ an automated tool to check the data quality or do it manually. With these downsides apart, DIY tools can cater to simple and small scale data requirements.  


  • Full control over the process
  • Prebuilt solution
  • You can avail support for the tools
  • Easier to configure and use


  • They get outdated often
  • More noise in the data
  • Fewer customization options
  • The learning curve can be high
  • Maintenance

Vertical-specific solution

You might be able to find a data provider catering to only a specific industry vertical. If you could find one that has data for the industry that you are targeting, consider yourself lucky. Vertical specific data providers can give you data that is comprehensive in nature which improves the overall quality of the project. These solutions typically give you datasets that are already extracted and is ready to use.

The downside is the lack of customization options. Since the provider is focusing on a specific industry vertical, their solution is less flexible to be altered depending on your specific requirements. They won’t let you add or remove data points and the data is given as is. It will be hard to find a vertical-specific solution that has data exactly the way you want. Another important thing to consider is that your competitors have access to the same data from these vertical-specific data providers. The data you get is hence less exclusive, but this may or may not be a deal-breaker depending upon your requirement.


  • Comprehensive data from the industry
  • Faster access to data
  • No need to handle the complicated aspects of extraction


  • Lack of customization options
  • Data is not exclusive
  • Not sufficient to get a big picture of the market

Data as a Service (DaaS)

Getting the required data from a DaaS provider is by far the best way to extract data from the web. With a data provider, you are completely relieved from the responsibility of crawler setup, maintenance, and quality inspection of the data being extracted. Since these are companies specialized in data extraction with a pre-built infrastructure and dedicated team to handle it, they can provide this service to you at a much lower cost than what you’d incur with an in-house crawling setup.

In the case of a DaaS solution, all you have to do is provide them with your requirements like the data points, source websites, frequency of crawl, data format, and the delivery methods. DaaS providers have the high-end infrastructure, resources, and expert teams to extract data from the web efficiently.

They will also have far superior knowledge in extracting data efficiently and at scale. With DaaS, you also have the comfort of getting data that’s free from noise and is formatted properly for compatibility. Since the data goes through quality inspections at their end, you can focus only on applying data to your business. This can greatly reduce the workload on your data team and improve efficiency.

Customization and flexibility are other great advantages that come with a DaaS solution. Since these solutions are meant for large enterprises, their offering is completely customizable for your exact requirements. If your requirement is large scale and recurring, it’s always best to go with a DaaS solution.


  • Completely customizable for your requirement
  • Takes complete ownership of the process
  • Quality checks to ensure high-quality data
  • Can handle dynamic and complicated websites
  • More time to focus on your core business


  • Might need to enter a long-term contract
  • Slightly costlier than DIY tools

Things to Factor In While Choosing a Data extraction solution

Data extraction solution for business

Customization Options

You should consider how flexible the solution is when it comes to changing the data points or schema as and when required. This is to make sure that the solution you choose is future-proof in case your requirements vary depending on the focus of your business. If you go with a rigid solution, you might feel stuck when it doesn’t serve your purpose anymore. Choosing a data extraction solution that’s flexible enough should be given priority in this fast-changing market.


If you are on a tight budget, you might want to evaluate what option really does the trick for you at a reasonable cost. While some costlier solutions are definitely better in terms of service and flexibility, they might not be suitable for you from a cost perspective. While going with an in-house setup or a DIY tool might look less costly from a distance, these can incur unexpected costs associated with maintenance. The cost can be associated with IT overheads, infrastructure, paid software, and subscription to the data provider. If you are going with an in-house solution, there can be additional costs associated with hiring and retaining a dedicated team.

Data Delivery Speed

Depending on the solution you choose, the speed of data delivery might vary hugely. If your business or industry demands faster access to data for survival, you must choose a managed service that can meet your speed expectations. Price intelligence, for example, is a use case where the speed of delivery is of utmost importance.

Dedicated Solution

Are you depending on a service provider whose sole focus is data extraction? Some companies venture into anything and everything to try their luck. For example, if your data provider is also into web designing, you are better off staying away from them.


When going with a data extraction solution to serve your business intelligence needs, it’s critical to evaluate the reliability of the solution you are going with. Since low-quality data and lack of consistency can take a toll on your data project, it’s important to make sure you choose a reliable data extraction solution. It’s also good to evaluate if it can serve your long-term data requirements.


If your data requirements are likely to increase over time, you should find a solution that’s made to handle large scale requirements. A DaaS provider is the best option when you want a solution that’s scalable depending on your increasing data needs.

When evaluating options for data extraction, it’s best to keep these points in mind and choose one that will cover your requirements end-to-end. Since web data extraction is crucial to the success and growth of businesses in this era, compromising on the quality can be fatal to your organization which again stresses the importance of choosing carefully.

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