Data driven career advice

Giving active and passive jobseekers new insights into the talent landscape.

At CareerBuilder we were sitting on a treasure trove of data. We had CVs, job postings and work force analytics. We had a solution (big data) with no user need to solve. We were tasked with finding an opportunity. This is our journey…

Our users

We ran interviews with 50 users over 2 quarters in 4 countries (UK, USA, Germany, France). They represented our key markets and while we had done plenty of research around their job search experience, until now, we had always put aside feedback around career progression. In these interviews users expressed their difficulties managing life and opportunities to develop professionally.

During a 2 day workshop in Paris we developed our set of personas, a subset of CareerBuilder's core persona groups. 

Using Lean UX

As part of our initial kick-off, we attended a Lean UX workshop run by Jeff Gothelf at Numa, Paris.

Having read the book and done the workshop, this project acted as a great opportunity to practice the methodologies and prioritise learning over delivery in our cross-functional team.


We didn't uncover everything up front. Our early designs exposed our ignorance in a field we held a strong self-confidence bias in. 

The process of pivoting when a hypothesis was falsified was embraced by the team as we loved the problem rather than our solutions.

Hiding the raw data

Users presented an expected behaviour in the absence of data but a peculiar response when it became available. I wrote more on this paradigm in an article entitled 'Building features nobody wants'.

Actionable insights

Showing users the information alone wasn't enough. They often needed a direct actionable insight to take from the data. It forced us to rethink how to present the data we were mining from our system, adding another layer of abstraction to it in order to make it useful.

How users compare

Users had a strong compulsion to compare themselves to their peers, especially their skills. They saw this as an opportunity to upskill and improve their career prospects.

Keep it simple

We really went mad experimenting with a plethora of visualisations. But when we ran A/B tests against our control (a bar chart), it won every time. Users understood the mechanics of a bar chart over a Voronoi chart, Sankey diagram or any other elaborate visualisation.

Lo-fi designs

We were able to get ideas onto paper and into the hands of users in minutes with mockups using balsamiq. This rapid prototyping allows our learning to speed up and build a shared understanding of the product we sought to build.

Micro experiments

CareerBuilder had available to them competing skills parsing engines. These algorythms looked at words in a PDF and matched them to skills where possible. We built a small experiment to test which users felt best represented their parsed CV. 

Users uploaded their CV, the parsing would take place with one of the three engines and then they would rank how relevant the tagged skills were. We used the data to later select one of the parsing engines as well as provide data to the teams who worked on these three competing engines.


As we progressed with each idea the fidelity of our prototyping increased. I used HTML prototyping tools in most instances to quickly make changes and utilise javascript for more dynamic interactions.

Skills experiment UI

We used this interface to stress test 3 different skill tagging engines.

Comparison UI

Comparing various data points to one another.

1 Page company report concept

An example of doing what users say rather than what they need.

Complex visualisations

One of several attempts to diversify our visualisations.

D3 chart visualisations

Iteration 50 looked like this.

Skill comparison UI

Using guages to give a high level skill match.

The end product

The live site registered around 250,000 visitors per month thanks to its prominent position on CareerBuilder’s global navigation. 2017 CareerBuilder launched ‘CareerInsights’ a replacement product that used the organisation’s visual design language.

This milestone is part of a strategy to design products off-brand and integrate only winning ‘big bets’ into the portfolio.

TYIT Ltd provides a full stack UX consultancy that designs accessible digital services. We've helped complex organisations like BEIS and DfE achieve digital transformation by running Lean and Agile discovery processes.

Companies House Number


13 Bright Rd Dunmow Essex CM6 3GU
© Copyright TYIT LTD 2019