Happy Car
How HAPPYCAR jump-started their recruiting process
Happy Car
About Happy Car
HAPPYCAR is the worldwide leading car rental comparison platform. HAPPYCAR compares different partners and provides the cheapest offers worldwide. The platform covers regions such as Germany, France, Netherlands, Spain, Italy, Poland, Switzerland, or the US.
Challenge
HAPPYCAR needs faster insights about candidates’ personality and communication behaviour during the hiring process. The goal is to increase the quality of candidates interviewed and to save time during the recruitment process
Solution
Especially, for customer care positions, getting quick insights about candidates’ personality upfront is key. Using an AI-video based personality solution helped to solve that problem.
Achievements
HAPPYCAR was able to reduce their time to hire at about 78% and improved their hire satisfaction rate at 40%.
HAPPYCAR found candidates in 3 easy steps
1. Candidates applying for a customer service position are asked to record a 1-minute video in addition to their traditional CV.
2. In the 1-minute video clip, candidates answer the question: “Why are you excited to work for HAPPYCAR?”
3. Videos are logged and analysed within the Retorio platform.
How Retorio made a difference
Retorio’s artificial intelligence derives a personality profile based on advanced psychological research, the Big 5 framework. The model classifies candidates according to 5 different personality dimensions, which are universally and interculturally accepted. Along with the personality profile, Retorio also provides a communication profile of the candidate. The combining profiles enable HAPPYCAR to receive an objective profile on all candidates, significantly accelerating the entire pre-selection process.
By The Numbers: Saved Time and Increased Hire Satisfaction
“We use Retorio to analyse our customer support candidates across all countries. The technology helps us to get fast insights and impressions in the preselection process.”
Results using Retorio
HAPPYCAR achieved time savings in the pre-selection process of customer support candidates by 78%. Simultaneously, they reduced the number of individual interviews held. Thus, talent operations gained more time in holding indepth, personal interviews. Moreover, they were 40% more satisfied with the new candidates after employment.