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45% of candidates are ghosted by recruiters in the UK, research suggests

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Over four in 10 (42%) UK candidates are ghosted by recruiters after a job interview, and 45% already after an initial conversation with a recruiter, a report from hiring platform Greenhouse has revealed…

Researchers also found that candidates from historically underrepresented backgrounds are 62% more likely to be ghosted after a job interview than white candidates.

When candidates are ghosted by recruiters it’s not what job seekers expect

Nearly nine in 10 (88%) candidates reported that they expected to hear back from companies within one or two weeks following their initialย application.

Kate Garbett, vice president for SMEs at Adecco Group, stated that ghosting candidates after a job interview was bad for organisational reputation.

Speaking toย HRย magazine, she said: โ€œThereโ€™s little justification for ghosting a candidate after an interview. It’s an unprofessional practice that can damage both a recruiterโ€™s and a companyโ€™sย reputationย and, more importantly, significantly affect a candidateโ€™s morale and motivation.

Reasons candidates are ghosted by recruiters?

โ€œNonetheless, it happens for a variety of reasons: time pressures, uncertainty about the candidateโ€™s fit for the role or the viability of the role itself, simply forgetting to close the loop, or just not knowing what to say.

โ€œUltimately, Iโ€™d urge anyone who interviews an unsuccessful candidate to take the time to explain why they are not being progressed.โ€

Meanwhile, the Greenhouse team found that 29% of candidates experienced a company changing the advertised salary after an interview.

Male candidates were 61% more likely to experience this than female candidates.

Reasons for candidates rejecting job offers

Candidates cited the top-three reasons they reject job offers as the salary being below their expectations (48%), having received a better offer from another company (32%) and limited or no flexible orย remoteย work options (21%).

Garbett commented that the findings revealed gender bias in salary expectations.

She said: โ€œThe finding that men in the UK are 61% more likely to experience a salary bait-and-switch compared to women is both worrying and surprising.

โ€œGiven the ongoing gender pay gap, itโ€™s usually accepted that men go for moreย payย rises and promotions than women, and are more prepared to negotiate hard for what they want financially.

โ€œIf bait-and-switch is happening disproportionately for men, it could indicate underlying biases or assumptions about gender and salary expectations.โ€

She added: โ€œThereโ€™s also evidence to suggest men dream bigger than women when it comes to pay so, if a salary range is advertised, could an explanation be that they assume that theyโ€™ll qualify for the higher figure?โ€

Diversity in recruitment benefits businesses

Ola Kolade, employment and skills director at Business in the Community, explained that eliminating bias during recruitment would benefit employers and employees. He added: โ€œEliminating biasย during the recruitment process and opening doors to diverse talent is not only the right thing to do; it has proven benefits for business too.

โ€œEmployers can eliminate bias by collecting diversity data during the application process to identify any potential barriers for diverse candidates, including diverse employees on interview panels, and making the recruitment processย accessibleย to everyone so no one gets left behind.”

Derek Mackenzie, CEO of Investigo, toldย HRย magazine that employers could eliminate bias by centering people in the recruitment process.

He said: โ€œRecruitment is ultimately about people, so people should be front and centre throughout the hiring process.

โ€œThereโ€™s a plethora of ways to eliminate this bias, namely bringing in regular human interaction throughout the process, whether it be curating job descriptions, analysing CVs or contacting candidates for interviews. That doesnโ€™t exempt potential human bias, but a representative hiring committee can reduce the potential for AI-driven bias.โ€