Technological developments over the past 10 years has provided recruiters with unprecedented access to ever more candidates and increasing amounts of information on their suitability for vacant positions. Candidate relationship management (CRM) systems heave with data pertaining to particular individuals such as contact details, CVs, recruiters’ notes and emails. The ability to accurately match a prospective candidate on the database with a job vacancy or specification is arguably the most important function that a CRM system performs.

The traditional method of harvesting CVs means that the information they contain is parsed and a record is created that typically populates structured fields like job category and core skills. Therefore, any keyword search carried out by a recruiter will pick up on relevant terms found in structured data in the database and return candidates who appear to be a good fit for the role.

Patently, the more familiar a recruiter is with a particular role or sector and the more adept they are at searching, the better the results. It is eminently possible, however, to miss a good candidate if a particular keyword or search term isn’t used. Moreover, perhaps the nugget of information that identifies that candidate as ideal for the role is buried in a piece of unstructured or raw data lying in the CRM that the keyword search can’t locate, such as the recruiter’s notes.

Having given the world of recruiting plenty of tools to go forth and find both active and passive candidates, along with the systems to store their details – the next challenge for software providers is to equip recruiters with superior search and match technology so they can extract maximum value from the candidate data that resides on their CRM systems. In many ways this has been the missing link up until now. This solution will come from some form of contextual searching capability that is able to search on unstructured or raw data – as well as structured data – and which bases its results on understanding what is contained within the text, rather than the filename or the fields associated with them. In short, it actually understands what the recruiter is looking for and is a far more intelligent form of searching.

Contextual searching represents the next generation of search for recruiters. This form of search does not have the potential risks and downsides associated with traditional keyword searches. If a candidate’s true unique selling point for the role is tucked away in a block of raw text in the database, a contextual search will discover it. Furthermore, its intelligent searching leaves the recruiter more time to get on with the business of recruiting.

Every recruiter needs a CRM system of some description, and while that won’t change going forward, they will increasingly look for one that can bring a competitive advantage. Providing superior search and match capabilities therefore, is likely to become a prerequisite, even though many recruiters might not at present be aware of this fact.

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