Skip to content

Case Study – The advantages of using AI for assessing voice and chat candidates

Case Study – The advantages of using AI for assessing voice and chat candidates

Share on facebook
Share on twitter
Share on linkedin
Chat and voice enabled AI assessments

LearningBranch Inc, April 2020

Background and Objectives

The client in this case study is a 7000-employee contact center company with global operations. Exceptional communication with customers is critical to their success. They require employees to have a high level of soft skills with advanced language proficiency in voice and chat processes.

The client experiences high turnover rates and large recruitment volumes, which is common in the industry. With over 500 recruitment tests every month, manual evaluation is too costly, time-consuming and inconsistent.

In 2019, the client approached LearningBranch with a request to automate the assessment of pre-hire candidates’ free speech and writing. The automated score would replace manual scoring on language proficiency and soft skills, and align with their existing rubric. The objectives were to reduce time, reduce cost, centralize reporting, and eliminate inconsistencies due to human bias common in manual evaluation processes.

Automating the evaluation process would save the client 250 resource hours per month.

The AI Assessment

LearningBranch has developed an AI assessment platform that automatically evaluates a candidate’s free speech and writing, including soft skills and language proficiency. The platform is cloud-based, cost-effective and fast. Assessment scores are returned immediately.

Using this platform, LearningBranch created an assessment that scores free writing responses to 10 different customer inquiries. Candidates from the client’s recruitment and training programs took the chat assessment.

The Results

The AI platform’s scores proved accurate 78% of the time, with the remaining tests less than 10% outside the acceptable range (95% of the time).

In addition, the platform removed inconsistencies and bias in human scoring.

Based on these results, the LearningBranch AI assessment has replaced the manually-scored communication test for one pre-hire program. This has immediately eliminated the time required to manually score over 100 tests per month. Once the assessment is fully deployed, it will save the client over 250 resource hours per month.

The client is now implementing the automated LearningBranch assessment throughout recruitment, training and operations.