Research

Research

Our Research-led recruitment model enables us to adopt a “deep dive” approach to identify and attract top talent who would otherwise be difficult to find.

Using an array of different technologies and techniques our highly experienced research function ensures that no stone is left unturned in the search for the ideal individual.

Our engagement rate with prospective candidates (the response rate to our approaches) is over 60% which is double the industry average.

We employ a variety of techniques, over multiple connection points, to assess prospective candidates and ensure that the fit is right from a professional, cultural and behavioural perspective.

Most candidates presented to our clients are high performers who are not actively looking for a move however are open to exploring the right opportunity.

We have invested significantly in a highly advanced technology stack to exponentially increase our ability to identify and contact top global talent in a highly responsive manner.

In addition to our extensive networks developed since 1998 we have access to:

  • the largest talent database in the marketplace where we can search over 1.2 billion professional profiles from 100+ data sources, including LinkedIn, at once.
  • 250 million+ hard-to-find candidate profiles in the most specialised industries.

Using proprietary technology and a network of commercial data partnerships we can access accurate contact information for 75% of the world’s professionals in seconds. Using Artificial Intelligence and publicly available information from billions of web pages, verification methods are continuously improved to deliver better data quality and accuracy.

Should advertising be desired, we have access to a network of 30,000 job sites with technology that uses AI to determine where the job should be published to reach the best fit candidates.

Contact Us

Don’t hesitate to contact us for more information

Battersea Power Station

The Engine Room

18 The Power Station

London

SW11 8BZ

Get in Touch

Please enable JavaScript in your browser to complete this form.