Finally, you’ll want to agree on a method for evaluating interviews on Spark Hire.
Whether you’re using Spark Hire’s evaluation system or your own scorecard, it’s important to create clear definitions on what you’re looking for in a particular response from a candidate.
For instance, let’s say you’re rating interview responses on a 5 star scale, you can use the following criteria to determine the rating and leave a comment to add more details about your rating. Please note that you’d still need to identify what you’re looking for in a response.
|Rating||When to use this rating|
|(5) ⭐⭐⭐⭐⭐||The candidate fully answered the question and their response went above and beyond what we’d be looking for.|
|(4) ⭐⭐⭐⭐||The candidate fully answered the question and their response met the expectations of what we’re looking for.|
|(3) ⭐⭐⭐||The candidate fully answered the question and their response was some of what we’re looking for.|
|(2) ⭐⭐||The candidate partially answered the question and/or their response and their response was some of what we’re looking for.|
|(1) ⭐||The candidate did not answer the question and/or their response is not what we’re looking for.|
Then, let’s say you’ve rated all interviews that were completed for a particular job, below is an example of criteria for when to mark that a candidate passed or failed the interview.
|Interview Result||Average Rating|
|Pass ✅||3.7 and up|
|Fail ❌||Under 3.7|
Mark the appropriate interview result in Spark Hire. From there, you can use the job and interview result filters to see everyone who should advance to the next round and everyone who should be rejected.
This is a simplification of the process, but our intention is to guide you in the right direction to come up with your own set of standards.