AI Case Study

Evernote doubles click-to-apply on Glassdoor and attracts ten to forty percent more candidates from underrepresented groups by optimising job descriptions using machine learning

With the help of Textio, Evernote started attracting more candidates from diverse backgrounds. Textio edits job descriptions and messages to a more neutral language. Evernote received 40% more applications from female candidates and 10% more from other underepresented groups.

Industry

Consumer Goods And Services

Media And Publishing

Project Overview

Textio is a data-driven platform that the company uses to write all of its job descriptions, and it gender-neutralizes language. Some words, Wagner explains, are huge turn-offs to women, and because of Textio, Evernote has received 25 percent more women applicants and has begun hiring men and women at an equal rate.

Reported Results

According to Textio:

* 60% of Evernote’s job posts reached a Textio Score of 90+ which means Evernote’s job listings will fill faster than 90% of similar listings
* Evernote’s click-to-apply rate on Glassdoor had more than doubled.
* Number of applications from underrepresented groups increased by 8-10%
* Upto 40% more female applicants

Technology

The algorithm scores job descriptions and messages on a 100-point scale

Function

Human Resources

Recruitment

Background

To ensure diversity in hiring Evernote used Textio's content creation AI to edit job postings

Benefits

Data

Data from 70 million job posts and hiring outcomes