The recruitment company increased the number of successful hires and improved the job matching algorithm.

Learn how GroupBWT helped a recruitment company improve the job matching algorithm and speed up the hiring cycle.

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The Client Story

Founded in 2011 in Europe, our client, a leading recruitment company, revolutionized recruitment by introducing innovative online methods. They have evolved into a global player with a powerful SaaS platform that uses advanced algorithms to seamlessly match job seekers with opportunities. With a strong tech background, their platform quickly became popular, helping companies find, hire, onboard, and manage better candidates faster.

From a startup with a visionary goal in 2011 to a European influencer in 2024, our client’s journey reflects steadfast dedication to reshaping the landscape of human resources.

Industry: HR
Cooperation: Since 2021
Location: Europe

Helped a recruitment company aggregate data from the most popular job boards to feed their AI-based job matching algorithm.

Quality data increased the accuracy of the AI-based job matching algorithm, leading to a 15% increase in hiring speed.


Aggregating vacancy data for AI-based job matching

We were approached by a large recruiting company that had developed its own job matching platform. They sought a solution to gather all available vacancies from numerous job boards based on specific criteria. It was crucial for them to access new vacancies promptly, necessitating a solution capable of real-time data collection and updates. Existing market solutions did not encompass the required number of job boards, prompting the decision to develop a custom data scraping platform.

Following the collection of vacancies, the platform’s AI model matches resumes from the database with the job vacancies database.

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The Solution

Custom data scrapers for popular job boards

We developed custom data scrapers for 10 job platforms and integrated the data aggregation framework into their existing SAAS platform.
Our solution ensured stable data collection, organized sequential data transformation for normalization and deduplication. We ensured data updates with the required frequency to guarantee the relevance of vacancies in the client’s database.

Additionally, we tailored data collection to specific search parameter requests according to business requirements. The system based on our data aggregation framework easily allows connecting to any data source. Support was also provided to make changes to the scraper if the source changes its structure.

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We have developed custom scrapers for the 10 most popular job boards and utilized our data aggregation framework to ensure a stable and high-quality data scraping process. Integrated with the client's SaaS platform for seamless data transition.

Alex Yudin
Web Scraping Team Lead
The Results

30% quicker selection and 15% more successful probation.

The speed of candidate selection for a vacancy increased by 30%, and the percentage of candidates who passed the probationary period increased by 15%.

The aggregation system led to more accurate recommendations for applicants and employers. The process of finding suitable vacancies accelerated due to timely data updates, resulting in more successful hires. This became a strong competitive advantage, allowing for better resource management and helping to expand the geographic scope of service provision.

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