With so many candidates in the market, it’s more important than ever to create an engaging and human candidate experience. But you need to balance that with finding the best talent for your role.
Skill testing can give recruiters a competitive advantage in today’s job market. Candidates who are hired on merit, rather than background, tend to stay longer and perform better over the long term. Here’s how to use skills assessments to fill your open positions, no matter how many applicants you are dealing with.
A skills test is an assessment used to provide an unbiased, validated evaluation of a candidate’s ability to perform the duties listed in the job description.
Typically, a skills test asks a variety of questions in different formats to see how candidates perform on-the-job tasks. A good skills test includes questions that are capable of being answered by someone already doing the job and can accurately measure key performance metrics. Questions should also be specifically tailored to relate to the responsibilities of an open position. Many skills tests include immersive experiences, like coding challenges or job simulations, to mimic how a candidate performs when faced with a real-life scenario.
Other types of job-readiness evaluations deploy validated psychometric assessments to identify those in-demand soft skills: things like motivation, conscientiousness, resilience, and emotional intelligence. A personality assessment varies from a skills test in that it predicts how a person will behave in a specific scenario, rather than their ability to complete a task.
Related: Should You Use Psychometric Tests for Hiring?
While skills test cover task-related abilities, like coding, copywriting, or sales, some pre-employment assessments integrate the less tangible capabilities – things like teamwork and leadership. These qualities are sought after by executives at more than 900 companies, according to a Wall Street Journal survey of executives.
Yet, 89% of those surveyed said they have a “very or somewhat difficult time finding people with the requisite attributes.” Where traditional hiring methods fall short, a skills test can easily clarify a candidate’s true talent.
“Many service companies, including retailers, call centers, and security firms, can reduce costs and make better hires by using short, web-based tests as the first screening step. Such tests efficiently weed out the least-suitable applicants, leaving a smaller, better-qualified pool to undergo the more costly personalized aspects of the process.”
Research by John Bateson, Jochen Wirtz, Eugene Burke and Carly Vaughan via Harvard Business Review
Overall, skills tests can play a critical role in predicting on-the-job success. More so than resumes or job interviews, a skills test can assess the true potential of a new hire to go the distance with the company. Here’s how skill testing works, and why more companies than ever are starting to integrate skill testing into the recruitment and hiring process.
Skill testing works best when the questions being asked are specifically crafted to the role and needs of the team hiring the new candidate. In designing a skills test, combine different types of questions to get a 360-degree view of how a candidate will perform in different scenarios.
There are a variety of ways to set up a skills test – and we’ll get into the mechanics of how to actually run the assessment in the next section. But, designing a thoughtful aptitude test takes some initial foresight on behalf of the hiring manager and team.
Research by Deloitte suggests this sample process for selecting and implementing skill testing questions:
Ultimately, the best use for a skills assessment is to help recruiters move away from the resume and allow candidates to prove they are the real deal. Crafting the right series of questions should be a collaborative process between the recruiting team and the team hiring the new employee. Here’s how these teams can set up and run a skills test.
In designing a skills test or pre-employment assessment, there are a few specific steps to take in order to thoughtfully structure your questions.
Based on our work with over 8,000 customers, we recommend following these best practices in setting up and running your skills test. These tips can help with candidate engagement and lead to high rates of completion.
We also suggest that video responses not be timed; there are too many technical issues that can result from a candidate trying to film a one-way video interview. If you do wish to set a time limit, make sure it’s at a minimum of five minutes.
Running a skills test through Vervoe, or any other platform, is relatively straightforward. Vervoe’s skills assessments let you select questions from a library of assessment tools, or design your own questions based on the specific needs of your company. The Expert Assessment Library offers questions and trials created by experts in their fields, meaning they have at least 3+ years of experience in their specific area of expertise. You can preview questions from any of the assessments and add them seamlessly through the Vervoe platform.
Now that you know how to set up an assessment, when should you deploy this tool during the hiring process?
Timing is everything when it comes to adding a skill assessment to your hiring process.
Research by Harvard Business Review revealed that skills tests should come early in the hiring process. According to their study, “Many service companies, including retailers, call centers, and security firms, can reduce costs and make better hires by using short, web-based tests as the first screening step. Such tests efficiently weed out the least-suitable applicants, leaving a smaller, better-qualified pool to undergo the more costly personalized aspects of the process.”
Skill tests should be used to screen candidates in, not out. The issue many recruiters face is that the volume of candidates makes it impossible to carefully consider each person’s ability. Smart algorithms and AI tools can turbo-charge candidate assessments by scoring results quickly and removing human bias from the equation.
Vervoe’s algorithm scores candidates using a multi-layered approach. Candidates are ranked based on how well they performed, rather than filtered out if they didn’t achieve a certain benchmark. The top candidates easily rise to the top; but no one misses out on being considered for the next round. When used early in the hiring process, skill tests can select a more diverse pool of applicants to continue onto the next phase.
There are many ways to set up a skills test, depending on the position for which you are hiring. Pre-employment skills tests can cover a range of positions: administrative assistant, finance and accounting, and call center reps are just a few roles that companies hire for using skills assessments.
Excel skill tests, coding skill tests, typing skill tests, and other computer skill tests are the most common forms of pre-employment assessments. Some companies focus on questions that are task-related, e.g. “Create a Powerpoint Slide that has a video embedded in the presentation.” Questions can get hyper-specific to test a niche skill, like a coding language, or be posed more broadly to test the general requirements for success at a certain level.
Some companies choose to focus on verifying the skills that will help a candidate succeed beyond the immediate position. This approach skews closer to a pre-employment assessment, with questions designed to reveal if a candidate can climb the corporate ladder, adapt in a challenging work environment, or respond under pressure.
For example, one call center rep test included questions such as, “You have an elderly customer on the phone who is having trouble understanding your instructions. A colleague is also trying to transfer a call from a customer you served before, and you have a scheduled follow-up call happening in 5 minutes. How would you handle and prioritize in this situation?”
Multiple choice, open-ended questions, and pre-recorded video responses are all great ways to see if a candidate has what it takes to do the job well. But, do candidates enjoy answering these types of questions?
By most accounts, candidates appreciate the opportunity to showcase what makes them great at their job. Orica, the world’s largest provider of commercial explosives, integrated skill-testing into their interview process to the delight of their job candidates. In revamping the interview process for graduate students looking to join the Orica team, recruiters consolidated their online evaluation components into one platform, Vervoe. The skill assessment combined questions focusing on skills, logic, and values.
An average of 86% of candidates completed the online process, and the reviews were mostly positive. Here’s what the candidates had to say about the skills test:
“The tests required total engagement and thought, and were a clear demonstration of what makes Orica different from any other company.”
“I think the questions were very diverse and it allowed me to showcase myself, my skills and abilities in different ways.”
“It gave me an opportunity to showcase who I am as well as challenge my skills”
This is just one example of how a skill test can change the entire interview process for a potential new hire. In a job market where people spend an average of 11 hours a week looking for a new job, it’s easy to get burned out, fast. Every job description starts to look the same; every interview begins to feel stale.
When given the opportunity to showcase their talent through real-world tasks, job candidates will jump at the chance to be engaged with the job description, rise above their resume, and challenge themselves. Companies that use Vervoe’s assessments experience a 97% candidate completion rate, which is among the highest engagement rates in the industry. Candidates love the opportunity to stand out from the crowd. Even if they aren’t hired, skills testing offers a break from the repetition of the stale interview experience.
The benefits of a skills test aren’t limited to the candidate experience.
Recruiters looking to hire diverse, high-performing teams with better efficiency and consistency can use pre-employment tests to their advantage. Skills tests are a better predictor of performance than resume screenings or traditional interviews alone. Resume screenings are bad for three reasons. First, studies suggest that it’s common for candidates to lie on their CV. The person you think you’re hiring may not actually possess the qualifications you think they do.
“We just wouldn’t be able to interview 2000 people in two weeks. But what we could do is utilize Vervoe to more accurately and in quite an unbiased way, assess everybody’s application during that period.
Rather than just assess the first 200 [applicants] and maybe hire 150 of them, Vervoe allowed us to actually assess all 3000 applicants in a two week period and still be able to select the best 150.”
Jeremy Crawford, Head of Talent Acquisition at Medibank
Second, resumes only provide a high-level view of a candidate’s credentials and work experience. These items don’t offer qualitative insight into actual on-the-job performance. Coupled with recruiting biases that are built into the process, the third threat is that recruiters are privileging candidates based on background and demographics, rather than talent. Perhaps this is why new hires crash out as often as they do. According to one study, 46% of new hires “fail” within the first 18 months of being hired.
Skill tests can help take some of the bias out of the interview process, give recruiters a new evaluation metric to consider, and lead to happier, long-term hires. There’s ample evidence to suggest they really do work better than many of the other traditional hiring methods recruiters have relied on in the past.
Related: How to Avoid the 12 Kinds of Hiring Bias
In our experience, skill testing works better than traditional hiring methods – with some caveats.
Without a doubt, aptitude tests can be used to replace resume screening. This style of sorting through candidates increases the chance that the best candidates will be unfairly eliminated. Good people get screened out, rather than screened in. So-called “pedigree proxies” – resumes and cover letters – are not indicative of job performance, yet they are often the quickest way a recruiter or algorithm can think of to cut down on their stack of candidate resumes.
Skills tests improve time to hire while allowing the hiring manager to see how someone will do the job, before they get the offer. This reduces turnover costs, which add up quickly: the cost of making the wrong hire can be up to 2.5x salary, easily over $100,000. Working with Vervoe’s skills assessments, on the other hand, can help a recruiter identify the best people at under $100 per hire.
The best skills tests, however, need the right formula to help the candidates succeed. Some recruiters focus narrowly on the skills that will help a new hire succeed in the immediate position for which they are hiring. Yet, many CEOs emphasize the importance of soft skills – things like leadership and teamwork.
Related: 5 Ways To Turn Rejected Candidates Into Allies
New hires may end up being disappointed and leaving because they lacked the soft skills needed to adapt to their new team, not necessarily the skills to perform the job. Recruiters must integrate questions into their skill assessment that focus on critical soft skills that predict long-term success. These validated psychometric assessments are key to assessing “culture fit” without defaulting to recruiter bias.
With any kind of assessment, there’s a common concern that’s quite commonly raised: is this assessment valid?
In summary:
There are many types of validity, and it’s rare that a test will satisfy every type. Looking specifically at tests for finding job fit, there are a few different types of validity that are particularly relevant, not just to ensure that the hire is a good one, but to ensure compliance with EEOC regulations.
In all cases where assessments are used, and in every step of the recruitment process, it’s essential that employers track and remain aware of differences in performance that are biased toward particular demographic factors. At Vervoe, we constantly monitor assessments to make sure candidates take tests that are fair, and based solely on skills that reflect how they would perform on the job.
In conclusion, we’ll leave you with few thoughts on skill tests compared to interviews.
First, interviews, in general, need a total overhaul. Recruiters have been asking the same, outdated interview questions for decades. Many candidates get overwhelmed by the performance anxiety inherent in the interview and may make (forgivable) mistakes. Nevertheless, many recruiters like the security of meeting someone before making an offer.
Many recruiters seek the same insight from a group interview or case study that they would get from an individual skill test. Unfortunately, using these methods can’t give you the same valuable information as a straightforward aptitude assessment. Case studies can be too conceptual; rather than seeing how a candidate will approach the work listed in the job description, case studies ask abstract questions. The goal of asking “how many tennis balls can fit on a Boeing 757” is not to see if the candidate can guess the right answer, but to see how they approach the question and reason through their response.
But this knowledge doesn’t always serve a recruiter with the best predictor of on-the-job success.
Group interviews provide more insight – into a candidate’s teamwork, leadership, and communication, for example. Yet, in a group scenario, extroverts tend to dominate. It can be difficult to see how each candidate performs as an individual while trying to consider the group at once.
In summary, skill testing is all about understanding whether a candidate can do something or knows something. It’s about verifying their ability to go the distance with your company. Pre-employment assessments differ slightly in that they focus on predicting how a candidate will behave in certain scenarios, not what they can do. By combining questions from skills testing and pre-employment assessments, recruiters can get a more accurate picture of the candidate’s ability.
There’s growing interest in AI-driven tools that infer skills from CVs, LinkedIn profiles, and other passive data sources. These systems claim to map someone’s capability based on the words they use, the jobs they’ve held, and patterns derived from millions of similar profiles. In theory, it’s efficient. But when inference becomes the primary basis for hiring or promotion, we need to scrutinise what’s actually being measured and what’s not.
Let’s be clear: the technology isn’t the problem. Modern inference engines use advanced natural language processing, embeddings, and knowledge graphs. The science behind them is genuinely impressive. And when they’re used alongside richer sources of data, such as internal project contributions, validated assessments, or behavioural evidence, they can offer valuable insight for workforce planning and development.
But we need to separate the two ideas:
The risk lies in conflating the two.
CVs and LinkedIn profiles are riddled with bias, inconsistency, and omission. They’re self-authored, unverified, and often written strategically – for example, to enhance certain experiences or downplay others in response to a job ad.
And different groups represent themselves in different ways. Ahuja (2024) showed, for example, that male MBA graduates in India tend to self-promote more than their female peers. Something as simple as a longer LinkedIn ‘About’ section becomes a proxy for perceived competence.
Job titles are vague. Skill descriptions vary. Proficiency is rarely signposted. Even where systems draw on internal performance data, the quality is often questionable. Ratings tend to cluster (remember the year everyone got a ‘3’ at your org?) and can often reflect manager bias or company culture more than actual output.
The most advanced skill inference platforms use layered data: open web sources like job ads and bios, public databases like O*NET and ESCO, internal frameworks, even anonymised behavioural signals from platform users. This breadth gives a more complete picture, and the models powering it are undeniably sophisticated.
But sophistication doesn’t equal accuracy.
These systems rely heavily on proxies and correlations, rather than observed behaviour. They estimate presence, not proficiency. And when used in high-stakes decisions, that distinction matters.
In many inference systems, it’s hard to trace where a skill came from. Was it picked up from a keyword? Assumed from a job title? Correlated with others in similar roles? The logic is rarely visible, and that’s a problem, especially when decisions based on these inferences affect access to jobs, development, or promotion.
Inferred skills suggest someone might have a capability. But hiring isn’t about possibility. It’s about evidence of capability. Saying you’ve led a team isn’t the same as doing it well. Collecting or observing actual examples of behaviour allows you to evaluate someone’s true competence at a claimed skill.
Some platforms try to infer proficiency, too, but this is still inference, not measurement. No matter how smart the model, it’s still drawing conclusions from indirect data.
By contrast, validated assessments like structured interviews, simulations, and psychometric tools are designed to measure. They observe behaviour against defined criteria, use consistent scoring frameworks (like Behaviourally Anchored Rating Scales, or BARS), and provide a transparent, defensible basis for decision-making. In doing this, the level or proficiency of a skill can be placed on a properly calibrated scale.
But here’s the thing: we don’t have to choose one over the other.
The real opportunity lies in combining the rigour of measurement with the scalability of inference.
Start with measurement
Define the skills that matter. Use structured tools to capture behavioural evidence. Set a clear standard for what good looks like. For example, define Behaviourally Anchored Rating Scales (BARS) when assessing interviews for skills. Using a framework like Sapia.ai’s Competency Framework is critical for defining what you want to measure.
Layer in inference
Apply AI to scale scoring, add contextual nuance, and detect deeper patterns that human assessors might miss, especially when reviewing large volumes of data.
Anchor the whole system in transparency and validation
Ensure people understand how inferences are made by providing clear explanations. Continuously test for fairness. Keep human oversight in the loop, especially where the stakes are high. More information on ensuring AI systems are transparent can be found in this paper.
This hybrid model respects the strengths and limits of both approaches. It recognises that AI can’t replace human judgement, but it can enhance it. That inference can extend reach, but only measurement can give you higher confidence in the results.
Inference can support and guide, but only measurement can prove. And when people’s futures are on the line, proof should always win.
Ahuja, A. (2024). LinkedIn profile analysis reveals gender-based differences in self-presentation among Indian MBA graduates. Journal of Business and Psychology.
Hiring for care is unlike any other sector. Recruiters are looking for people who can bring empathy, resilience, and energy to the most demanding human roles. Whether it’s dental care, mental health, or aged care, new hires are charged with looking after others when they’re most vulnerable. The stakes are high.
Hiring for care is exactly where leveraging ethical AI can make the biggest impact.
The best carers don’t always have the best CVs.
That’s why our chat-based AI interview doesn’t screen for qualifications. It screens for the the skills that matter when caring for others. The traits that define a brilliant care worker, things like:
Empathy, Self-awareness, Accountability, Teamwork, and Energy.
The best way to uncover these traits is through structured behavioural science, delivered through an experience that allows candidates to open up. Giving candidates space to give real-life, open-text answers. With no time pressure or video stress. Then, our AI picks up the signals that matter, free from any demographic data or bias-inducing signals.
Candidates’ answers to our structured interview questions aren’t simply ticking boxes. They’re a window into how someone shows up under pressure. And they’re helping leading care organisations hire people who belong in care and those who stay.
Inclusivity should be a core foundation of any talent assessment, and it’s a fundamental requirement for hirers in the care industry.
When healthcare hirers use chat-based AI interviews, designed to be inclusive for all groups, candidates complete their interviews when and where they choose, without the bias traps of face-to-face or phone screening. There are no accents to judge, no assumptions, just their words and their story.
And it works:
Drop-offs are reduced, and engagement & employer brand advocacy go up. Building a brand that candidates want to work for includes providing a hiring experience that candidates want to complete.
Our smart chat already works for some of the most respected names in healthcare and community services. Here’s a sample of the outcomes that are possible by leveraging ethical AI, a validated scientific assessment, wrapped in an experience that candidates love:
The case study tells the full story of how Sapia.ai helped Anglicare, Abano Healthcare, and Berry Street transform their hiring processes by scaling up, reducing burnout, and hiring with heart.
Download it here:
A new study has just confirmed what many in HR have long suspected: traditional psychometric tests are no longer the gold standard for hiring.
Published in Frontiers in Psychology, the research compared AI-powered, chat-based interviews to traditional assessments, finding that structured, conversational AI interviews significantly reduce social desirability bias, deliver a better candidate experience, and offer a fairer path to talent discovery.
We’ve always believed hiring should be about understanding people and their potential, rather than reducing them to static scores. This latest research validates that approach, signalling to employers what modern, fair and inclusive hiring should look like.
While used for many decades in the absence of a more candidate-first approach, psychometric testing has some fatal flaws.
For starters, these tests rely heavily on self-reporting. Candidates are expected to assess their own traits. Could you truly and honestly rate how conscientious you are, how well you manage stress, or how likely you are to follow rules? Human beings are nuanced, and in high-stakes situations like job applications, most people are answering to impress, which can lead to less-than-honest self-evaluations.
This is known as social desirability bias: a tendency to respond in ways that are perceived as more favourable or acceptable, even if they don’t reflect reality. In other words, traditional assessments often capture a version of the candidate that’s curated for the test, not the person who will show up to work.
Worse still, these assessments can feel cold, transactional, even intimidating. They do little to surface communication skills, adaptability, or real-world problem solving, the things that make someone great at a job. And for many candidates, especially those from underrepresented backgrounds, the format itself can feel exclusionary.
Enter conversational AI.
Organisations have been using chat-based interviews to assess talent since before 2018, and they offer a distinctly different approach.
Rather than asking candidates to rate themselves on abstract traits, they invite them into a structured, open-ended conversation. This creates space for candidates to share stories, explain their thinking, and demonstrate how they communicate and solve problems.
The format reduces stress and pressure because it feels more like messaging than testing. Candidates can be more authentic, and their responses have been proven to reveal personality traits, values, and competencies in a context that mirrors honest workplace communication.
Importantly, every candidate receives the same questions, evaluated against the same objective, explainable framework. These interviews are structured by design, evaluated by AI models like Sapia.ai’s InterviewBERT, and built on deep language analysis. That means better data, richer insights, and a process that works at scale without compromising fairness.
The new study, published in Frontiers in Psychology, put AI-powered, chat-based interviews head-to-head with traditional psychometric assessments, and the results were striking.
One of the most significant takeaways was that candidates are less likely to “fake good” in chat interviews. The study found that AI-led conversations reduce social desirability bias, giving a more honest, unfiltered view of how people think and express themselves. That’s because, unlike multiple-choice questionnaires, chat-based assessments don’t offer obvious “right” answers – it’s on the candidate to express themselves authentically and not guess teh answer they think they would be rewarded for.
The research also confirmed what our candidate feedback has shown for years: people actually enjoy this kind of assessment. Participants rated the chat interviews as more engaging, less stressful, and more respectful of their individuality. In a hiring landscape where candidate experience is make-or-break, this matters.
And while traditional psychometric tests still show higher predictive validity in isolated lab conditions, the researchers were clear: real-world hiring decisions can’t be reduced to prediction alone. Fairness, transparency, and experience matter just as much, often more, when building trust and attracting top talent.
Sapia.ai was spotlighted in the study as a leader in this space, with our InterviewBERT model recognised for its ability to interpret candidate responses in a way that’s explainable, responsible, and grounded in science.
Today, hiring has to be about earning trust and empowering candidates to show up as their full selves, and having a voice in the process.
Traditional assessments often strip candidates of agency. They’re asked to conform, perform, and second-guess what the “right” answer might be. Chat-based interviews flip that dynamic. By inviting candidates into an open conversation, they offer something rare in hiring: autonomy. Candidates can tell their story, explain their thinking, and share how they approach real-world challenges, all in their own words.
This signals respect from the employer. It says: We trust you to show us who you are.
Hiring should be a two-way street – a long-held belief we’ve had, now backed by peer-reviewed science. The new research confirms that AI-led interviews can reduce bias, enhance fairness, and give candidates control over how they’re seen and evaluated.