In 2016, a major insurance and asset management firm began testing the utility of pymetrics for hiring effective Sales Agents. They were hoping to significantly improve retention and performance issues, as well as enhance employer branding.

To establish the “success profile” for a Sales Agent, 50 incumbent employees with strong sales revenue were identified to complete the pymetrics assessment. This data was subsequently used to train a custom model to make hiring recommendations that specifically reflected the needs of the role. During the initial study period, the firm opted to have 134 active employees (who had been hired using the conventional process) complete the pymetrics assessment.

After 10 months, the employees that pymetrics deemed very strong fits for the role were found to have 28% higher sales than those that pymetrics did not recommend.

Upon collecting an additional six months of data, the firm also examined the effects on predicting tenure. Sales Agents that had not been recommended by pymetrics were 46% more likely to leave the firm than those who were deemed to be a very strong fit. Regardless of how long employees stayed in their roles, highly-recommended Sales Agents yielded 33% more sales per year.

One survey of candidates that completed an application for the Sales Agent role indicated that 77% enjoyed the process and 89% would recommend it to other jobseekers. Recruiters were even more optimistic about pymetrics’ effect, with 92% believing the assessment added value to the hiring process.