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How does matching work?

What is Matching?

Matching is the technology that powers the personalised experience across urfuture.

Rather than showing every candidate the same jobs, urfuture analyses each person's behavioural profile and compares it against careers and job opportunities to identify the roles they are most likely to enjoy, perform well in, and stay in long term

This creates a personalised experience where every candidate sees recommendations that are unique to them, similar to how platforms like Spotify recommend music or Netflix recommends films and TV shows.

How does Matching work?

Once a candidate completes their Career Match assessment, urfuture builds a behavioural profile using their personality, motivations and Working Traits.

This profile is then compared against scientifically developed behavioural profiles for different career pathways and the requirements of individual jobs.

The result is two types of personalised recommendations:

  • Career Matches – showing which careers best align with the candidate.
  • Job Matches – showing how well they match each vacancy on the platform.

Every recommendation is unique to the individual, meaning two candidates applying for the same role may receive different Job Match scores based on how well their behavioural profile aligns with the role.

What is a Career Match?

A Career Match measures how well a candidate naturally aligns with a particular career area.

For example, a candidate may receive strong matches for:

  • Engineering
  • Sales
  • Marketing

These recommendations are based on behavioural compatibility rather than qualifications or previous experience.

Career Matches are designed to help candidates explore careers that fit who they are as a person, reducing confusion and providing better career guidance.

What is a Job Match?

Once a candidate has Career Matches, urfuture also calculates a Job Match for every vacancy on the platform.

A Job Match combines:

  • The candidate's behavioural profile.
  • Their Working Traits.
  • The requirements selected by the employer for that specific job.

Every job therefore receives its own personalised match score for every candidate.

This means two candidates looking at the same vacancy may receive completely different Job Match scores because the role suits them differently.

Job Matches help candidates focus on opportunities where they are most likely to succeed while helping employers prioritise candidates who are the strongest behavioural fit.

How can employers use Matching?

Matching provides employers with richer data than a traditional recruitment process.

Within the urfuture platform, employers can:

  • View every candidate's Career Match scores.
  • View personalised Job Match scores.
  • Understand why a candidate has been matched.
  • Filter candidates using Working Traits.
  • Build custom Job Matches for every vacancy.
  • Reduce manual screening by prioritising the strongest behavioural matches.

This enables faster, more consistent and more informed hiring decisions.

How can candidates use Matching?

Matching helps candidates:

  • Discover careers they may not have considered.
  • Understand their natural strengths.
  • Find jobs that suit how they prefer to work.
  • Spend less time applying for unsuitable roles.
  • Increase the likelihood of finding a career they'll enjoy.

Rather than searching through hundreds of vacancies, candidates receive personalised recommendations based on who they are.

Is the Matching algorithm scientifically developed?

Yes.

urfuture's matching framework was developed using behavioural science in collaboration with a Chartered Psychologist from the University of Oxford.

The framework was built using:

  • 500 hours of research interviews.
  • 400 individual opinions.
  • 159 organisations.
  • 18 career pathways.

This research created the behavioural profiles that underpin urfuture's Career Matching technology.

How will Matching improve over time?

urfuture's current matching model is built on behavioural science.

As more candidates are successfully placed into jobs, the platform will learn from real-world outcomes.

By combining behavioural science with machine learning and AI, urfuture aims to continually improve the accuracy of its recommendations based on factors such as successful placements, job performance and long-term retention.

This evolution will enable increasingly predictive matching, helping candidates discover careers they'll thrive in while helping employers make better hiring decisions.