Glassdoor is a leading online platform for job seekers and employers, offering millions of reviews, ratings, salaries, and insights on companies and workplaces. But how did Glassdoor improve its user experience and engagement? The answer lies in its use of artificial intelligence and natural language processing to create a smarter and more personalized job search and employer branding.
The Challenge
Glassdoor wanted to help its users find the best jobs and companies for them, as well as help employers attract and retain top talent. However, it faced several challenges in matching users with relevant and high-quality content, such as:
- The diversity and complexity of user queries and preferences
- The variability and ambiguity of job titles and descriptions
- The difficulty of measuring and comparing employer reputation and culture
The Solution
Glassdoor applied AI and NLP techniques to enhance its platform in various ways, such as:
- Developing a semantic search engine that understands the meaning and intent of user queries and provides more accurate and relevant results
- Creating a job title normalization system that standardizes and categorizes job titles based on skills, experience, and industry
- Building a company rating system that analyzes user reviews and ratings and generates scores for various aspects of employer reputation and culture
- Designing a job alert system that notifies users of new and matching job opportunities based on their preferences and behavior
The Value
Glassdoor’s use of AI and NLP enabled it to improve its user satisfaction and retention, as well as its employer value proposition. Glassdoor reported that:
- Its semantic search engine increased user engagement by 30% and reduced bounce rate by 10%
- Its job title normalization system increased click-through rate by 41% and conversion rate by 8%
- Its company rating system increased user trust and confidence by 25% and employer brand awareness by 15%
- Its job alert system increased user loyalty by 35% and application rate by 12%
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