“ScraperAPI makes it so easy to collect data on a large scale from every website in a proper format. It is reusable and saves time. We could hire a person to scrape data manually or even a developer to build us a scraper. But none of these options beat ScraperAPI’s out-of-the-box solution. It just works.”
saas.group is a portfolio company for profitable, bootstrapped SaaS businesses. Between 2017 and 2023, it acquired 16 of these companies, including AddSearch, Seobility, and yours truly: ScraperAPI — with many upcoming deals in the pipeline.
Despite the company’s impressive track record, finding subscription-based, product-led models to acquire wasn’t always a straightforward process for Dirk Sahlmer, Head of Origination at saas.group, and the rest of the M&A team.
Dirk and the team initially used traditional data platforms to pull company information from PR reports, LinkedIn, and other social media platforms — but soon discovered that these sources didn’t cover companies that matched saas.group’s ICP.
Their M&A research process was inefficient and cumbersome. Ideal acquisition opportunities were slipping through the cracks — something had to change. The team needed a more effective way to find the right acquisition prospects quickly.
Lots of companies within our target group were flying under the radar because they’re not that active on social media. For example, they haven’t raised any funding rounds, so there’s a lack of data points. Even large data platforms could not provide good coverage for our target group.
Dirk Sahlmer
Head of Origination at saas.group
I would say by just populating a list of similar websites, ScraperAPI saves me an hour or two of my day. Before, it would take me an hour or two to populate a list of 50 companies. Now, I can do this in a few seconds.
Dirk Sahlmer
Head of Origination at saas.group
Instead of paying for expensive data aggregation platforms or settling for free alternatives, Dirk used ScraperAPI to build an internal database of potential prospects.
He provides a URL to ScraperAPI, and it returns the results as a chasing file. Then Dirk imports the chasing files into Google Sheets via open-source software. This setup automatically structures the data and puts them line by line — populating the table.
This process sounds complex, but it’s pretty straightforward to pull off. You don’t need any advanced programming knowledge to use ScraperAPI.
Dirk and his team have unlocked a new level of efficiency thanks to ScraperAPI.
But more than saving time, ScraperAPI helps saas.group to discover viable acquisition opportunities that would have otherwise stayed hidden. In Dirk’s words, “It’s impossible to quantify this benefit.”
Interested in seeing how ScraperAPI can help you overcome your data collection challenges?