How to Give Great Interview Feedback
Post-interview, giving timely, useful feedback helps create a good candidate experience, and it can strengthen your employer brand too. Here are some dos and don’ts to make sure your feedback is built on a solid foundation.
Give concise, actionable feedback
Your feedback is only useful to a candidate if they can act on it in the future, so make sure what you’re offering is instructive and concrete. Steer away from vague evaluations and try to give specific examples of when the candidate showed particular strengths and weaknesses.
Out of respect for the candidate’s time – and your own – keep the feedback brief and tightly focused. After all, the document is only one company’s verdict and will be one of several factors in their overall jobseeking strategy.
You might find that the job description for the role, or an interview question list, if one was used, can be a helpful framework for constructing your feedback and making sure all the key points are covered.
Cover the whole hiring process
Feedback shouldn’t just come from the hiring manager. To provide good-quality post-interview feedback, it’s important to tap into the whole interview and recruiting process to gain a representative overview of the candidate’s performance. This is especially true when the candidate experience involves many steps, such as questionnaires, video interviews, first and second round in-person interviews and skill tests.
Get the timing right
It’s important to collect feedback while the interview experience is fresh in people’s minds, but not so soon that they haven’t had time to process and are still mentally sifting through first impressions. 24 hours after the interview is a good ‘sweet spot’ to aim for.
Another good reason for collecting feedback a day later is that there’s less chance of people discussing the candidate and influencing one another’s opinions, as over time they could develop a group consensus which can skew your data.
Collect high-quality candidate feedback data
Asking for candidate feedback in an open-ended way is likely to bring in a weird and wonderful assortment of emails, chats, in-person comments and more. It’s all valuable, but collating it into a single verdict is pretty much impossible.
Surveys can be an invaluable tool here – a set format can help you collect like-for-like data from stakeholders across your business, so that it’s easy to collate useful feedback for candidates who’ve been through the interview process. Question formats like multiple choice or ranking can improve consistency and reduce effort for everyone involved.
The same goes for collecting candidate feedback. A survey provides a set format that’s easy for you to construct and for candidates to complete. It also makes sure you receive data in a consistent format.
As with the final feedback format, you could use the job description or interview question list as a structure for your feedback questionnaire.
Give feedback without making sure it’s welcome
For many candidates, feedback after an interview is a valuable tool for their future job search strategy, and a way for companies to recognize and pay back the time and effort they’ve put into an application. But for some people, they prefer to simply move on when an application is unsuccessful.
Before issuing feedback, check with the candidate that they would like to receive it. You could add this as an early checkpoint in your applicant tracking process, such as during an application questionnaire.
Allow personal biases to skew the picture
It’s just human nature – regardless of how good your interview skills are, it’s almost impossible to be totally objective about every applicant in the talent pool. Sometimes we develop a personal preference for one candidate over another, or allow our experiences to unconsciously bias us against well-qualified candidates.
By bringing AI tools into the picture, these unhelpful subjective traits can be eliminated so that feedback is based on competence, performance and experience, rather than irrelevant factors such as age, gender or ethnicity.
Analyzing the results of your candidate feedback surveys using AI means that when you come to deliver your feedback, you can be sure you’re offering the candidate a fair and balanced picture of why they did or didn’t progress in the hiring process.