Three ways to make money with web scraping as a freelancer
Monetize your web scraping skills by leveraging online platforms
Before diving into this article, let me remind you about the Prague Crawl summit in Prague this Wednesday.
Secure your seat now and let’s meet there.
Until a few years ago, a freelancer who wanted to make some money with web scraping didn’t have so many options. He should enter the global job market using freelancing platforms and compete against other professionals to win some contracts.
While this is still true today, and it’s still the first way professionals use to make money, we now have more options to increase our income by adding additional revenue streams.
In this article, we’ll see how to leverage an online platform to maximize revenues with almost no effort.
Before proceeding, let me thank NetNut, the platinum partner of the month. They have prepared a juicy offer for you: up to 1 TB of web unblocker for free.
Custom Projects (Freelance Gigs)
As we mentioned before, the most immediate way to make money is by taking on custom web scraping projects through freelancing platforms. Well-known marketplaces like Fiverr, Freelancer.com, and Upwork have numerous clients posting jobs for data extraction.
In fact, at any given time, Upwork alone lists thousands of open web scraping jobs (over 2,600 as of this writing).
Platforms like these connect you with businesses or individuals who need specific data scraped for purposes such as market research, lead generation, price monitoring, or content aggregation.
The process is similar on every platform: first, you need to build a compelling profile, and then you can start searching for gigs that match your skills.
To stand out in this competitive market, highlight your technical skills (programming languages, scraping frameworks, proxies/anti-block experience) and include any portfolio examples of past scraping work.
If you’re new and lack client reviews, you can build credibility by using a public website as a sample project and showcasing the results (for example, a sample dataset or screenshots of the scraper in action).
Make sure to clarify the types of websites you can handle (e.g., e-commerce sites, directories, social media, etc.) and mention delivering data in clean formats (CSV, JSON, Excel).
Because freelance platforms are global and competitive, consider niching down your expertise. For example, you might brand yourself as an expert in scraping real estate sites, or aggregating product prices, or collecting social media stats. This helps attract clients looking for those specific needs.
Also, respond quickly to inquiries, communicate clearly, and be realistic with timelines. Positive reviews and ratings from early projects will significantly boost your profile.
Being selected for a task can be as hard as the work itself, but freelancing can help you grow your skills and build relationships with satisfied customers, who can refer new ones directly or via feedback on the platform.
Thanks to the gold partners of the month: Smartproxy, IPRoyal, Oxylabs, Massive, Rayobyte, Scrapeless, SOAX and ScraperAPI. They’re offering great deals to the community. Have a look yourself.
From today, we’re also adding Syphoon to our partners. Please have a look at their site.
Data Marketplaces (Selling Datasets)
After you finish your freelancing gig and you deliver the code of the scraper (or the dataset) to your customers, you have done all the hard stuff. But do you know that with some extra effort, you can monetize your work in other ways?
First, you can sell the datasets on data marketplaces; you just need to run the scraper and adapt the output to the platform's rules. Let’s see some of them.
Datarade
This is a solution more suitable for web data companies than for freelancers, since, as I recall, it has costs associated with being listed on their website.
Data buyers can look for datasets, not only web data, and then contact the vendor directly for further enquiries, following a traditional B2B buying cycle.
In this case, we can see that the marketplace helps with the discovery phase of datasets, but does not handle data delivery, quality, or purchase.
AWS Data Exchange
Just like Datarade, AWS Data Exchange is a solution for promoting datasets to a broader audience. Just like we’ve seen before, since the platform hosts every type of data, it helps in the discovery phase of datasets and with delivery. However, there is no quality control over the data, and purchases occur off the website.
On the platform, you’ll find mostly data companies, but since it’s free to join, nothing stops a freelancer from listing their datasets there, after completing the seller onboarding.
Data Boutique
As the founder of Data Boutique, I must mention it. The platform is merely focused on web data, in particular, the “clean side” of it: no personal information involved, and only public factual data not subject to copyright.
The platform is open to freelancers, companies, and websites themselves that want to monetize data extractions. Sellers can choose what to sell and upload it to the platform, or they can compete for open bids opened by buyers.
The platform tests data quality and manages both payment and file delivery, so buyers can purchase datasets with just a few clicks.
Listing on any data marketplace is not a guarantee of success: depending on the website’s traffic and the discoverability of your datasets, you can have more or less success. Listing famous websites can be a good strategy, but usually, there’s more competition and alternatives on the market, while niche websites can be more rewarding.
For this reason, the best way to approach a data marketplace is to list what you’re already scraping, so you don’t incur additional costs and can potentially generate more revenue for your business.
Scraping Marketplaces (Selling Scrapers as Tools)
The third strategy is to sell the scraper itself rather than the data. There are dedicated marketplaces where developers can publish web scraping tools or bots and earn money when others use them. A prime example is the Apify Store, which has emerged as a leading platform for buying and selling ready-made web scrapers, automation scripts, and APIs.
Apify Store
Apify allows developers to create Actors (cloud-hosted scraping and automation scripts) and list them in an app-store-like catalog.
In Apify’s own words, “You can publish your web scraper, set a price, and get paid when Apify users use your scraper”.
The marketplace hosts thousands of such Actors (over 4,500 community-built Actors as of 2025), and hundreds of developers are monetizing their code. Apify handles the execution of the scraper in the cloud and charges users for usage, sharing a portion with the developer.
The model is often subscription-based – a user might pay a monthly fee to access your scraper with certain usage limits. This makes it an attractive passive income avenue for talented scraper developers.
You will probably need to create an “actor” version of your scraper, integrating Apify features into your code. However, with a bit of effort, you can earn passive income each time someone uses your code.
RapidAPI
Probably this is the most demanding approach, but it’s worth mentioning. Once you have developed your scraper, you can also package it as an API and sell it on API marketplaces like Rapid API.
This is not suitable for scrapers with long executions, but if you’re able to create one that queries a specific URL, it can be a good move.
Just like for data marketplaces, listing your software on a platform is an investment with uncertain returns. You don’t know what will work and how many customers you will get from your listings, but if you’re ready for this effort, you can add a third revenue stream for the same scraper built for your customer of the freelancing gig.
How to list a dataset on Data Boutique
Let me show you how to list your dataset on Data Boutique, since it’s the platform I know more about, for obvious reasons. We’ll use the Zillow dataset we created last Thursday as an example.
The first thing we need to do, after completing your seller onboarding procedure, is browse the Data Boutique website and look for the website we’re willing to sell, using the “Search by Website” menu.
In our case, the website is listed, but if you cannot find it, you can always ask for it.
On the Zillow page, you’ll find out if there’s already someone selling some datasets on it and a button for applying your dataset.
After clicking it, you will be prompted with a series of questions about your scraping process, the final price of the dataset, its refresh policy, and other stuff. I’d like to focus on two main aspects of the datasets: pricing and refresh policy.
Pricing a dataset on Data Boutique
On Data Boutique, the sellers set the price, with no boundaries. The platform hosts datasets that range from $ 5 USD for smaller and simpler extractions to $3,000 USD for Airbnb data from an entire country.
When setting a price, please remember two factors:
Your first competitor is the potential buyer who could decide to do it by themselves or go on Upwork and ask for the dataset. So it should be a balance between your costs for extraction and the “no-brainer” for the buyer.
The platform takes a 30% fee on every dataset sold, so be aware of it when setting the price.
The transaction fee model ensures that the interests of the platform and its actors are aligned. Data Boutique makes money when sellers sell their datasets, so that’s the most important KPI that we want to maximize. To do so, buyers should also be willing to buy, so they can spend more on the platform. The more money sellers make, the more Data Boutique makes.
Setting a refresh rate policy
Among the different questions you’ll be prompted, there’s one about the refresh policy of the dataset.
While buyers will be more tempted to buy fresh datasets, we understand that keeping up and running an extraction that no one is actually buying is a cost.
For this reason, if you want to test the waters and see if an extraction you’re ready to make can be interesting, you can set the refresh policy as “On Demand”.
It basically means that you’re ready to provide a listed dataset in ten days from the first purchase.
Instead, if you already have the dataset and don’t plan to refresh it unless there’s a sale, you can say you’re uploading a static dataset.
If you’ve already got operations in place that refresh the dataset on a certain frequency, you can declare you’re selling a daily/weekly/monthly refreshed dataset. Keep in mind that if the datasets don’t get refreshed according to the declared frequency, they will be downgraded until they become static.
Of course, sending the datasets on a regular basis to Data Boutique is a challenge, but it has its rewards.
If your publishing calendar is regular enough, the platform gives buyers the opportunity to buy historical data.
Listing a dataset
After we complete our questionnaire for selling a dataset, we’ll have all the details needed to start selling.
What we should care about the most is:
The data schema: This is the data structure that we need to follow for our datasets. Each data schema has a list of columns that should be placed in the exact order as mentioned in the schema documentation.
The file delivery guide: the set of rules and syntax to use to send the file on the platform correctly
Your AWS credentials: You’ll be assigned a pair of AWS credentials to use in your scripts. Since all file transfers occur via AWS S3, you will need to create a script to upload the files to a specific S3 bucket and key.
In our Zillow example, we’ve been assigned the schema REAL-ESTATE-BASIC, which contains a sort of minimal information about real estate listings.
What I did in the code was to simply match the output of our scrapers from the documentation page with the field list for data providers.
In this way, after the scraper terminated, I just needed to send the output to the path declared in my contract page via S3, including my user ID and the contract ID.
After all the quality controls were passed, the dataset was listed successfully.
Conclusion
Making money as a freelancer in web scraping is hard: the competition is fierce and global, and you’re usually trading your time for work to complete tasks for your customers.
In this landscape, adding passive income by maximizing the number of revenue streams available is key to extracting more value from your work.
I hope this small guide has helped you to show you more options for reaching your financial goals through your web scraping skills.