creating a personalised job feed for job seekers
By: Joshua Koomen
Tags: Recommendation System, Smart Matching Algorithm, Human Centred Design, UX, Interaction Design

For Tempo-Team, a Dutch HR website with 300.000 active users, I am continuously improving the UX for matching users with the jobs we offer, based on profile data.

current situation

finding the right job isn’t easy

Despite the fact the website knows a lot about the users, it doesn’t yet represent this on the relevant parts of the website. While frequently testing the user experience, I found out that the lack of smart matching makes it hard for users to stay confident in their search of a job they love. So every step in our development that would lead to a better match, would make a big difference for the user experience.

If you were a technician, living in Amsterdam, you would expect the platform to lead you to the right jobs. Especially when you already registered and uploaded your resume. However, the user now has to actively seek for the right jobs on the job board.

this leads to…

users feeling that they won’t find the right job.

users responding to jobs that don’t fit their needs, rather than the jobs that do match their needs and expectations.

current situation, a rather anonymous selection of jobs

future situation

personalised recommendations

Personalised jobs has the potential to increase user satisfaction. Good recommendations help users quickly identify items that interest them and helps to grow the loyalty for your brand. Users are likely to return to websites to make it more simple to find the relevant content. In this case, jobs.

Encourage engagement with recommendations by presenting them prominently, segmenting suggestions into clear categories, and providing methods for users to give feedback. — NN group

because you watched — Netflix

recommendations - Amazon

application for job feed

I created the design that suggests the right jobs, based on the users’ preferences and competences. This approach would really help the user find a more suitable job they trust, as we found out during interviews with visitors of this website.

recommended vacancies (aanbevolen vacatures) , matching the users’ profile. These are the first cards the user sees on the page. They contain a star icon followed by a message saying “found for you”.

, matching the users’ profile. These are the first cards the user sees on the page. They contain a star icon followed by a message saying “found for you”. segmentations , to make a clear distinction between recommendations and all other vacancies.

, to make a clear distinction between recommendations and all other vacancies. primary button, making the recommended vacancies stand out of the regular vacancies.

The great thing about the feed is, that the user doesn’t have to actively filter through all the jobs, as the website is showing all relevant jobs based on their profile. It’s like Netflix, but then for jobs. Isn’t that amazing?

measuring the impact of the design

a/b/c/d testing

Multivariate testing is an expansion of a/b testing in which more than 2 variants are tested and compared. This enabled us to test multiple variations of the recommended vacancies at once, and how they eventually lead to a successful job application.

We made small changes in the button types and copy, to see what works best for our users. I chose the next variants to test:

a — button, label: found for you

b — button, label: based on your profile

c — text link, label: based on your profile

d — text link, label: found for you