To suggest a new product feature that could help Glassdoor acquire its next 10 million customers, I propose the implementation of a personalized job recommendation system. This system would use machine learning algorithms to analyze user behavior on the Glassdoor platform, such as the types of jobs they search for, the companies they follow, and the job listings they save. Based on this data, the system would then provide personalized job recommendations tailored to each user's interests and career goals. This feature would be beneficial to both job seekers and employers. For job seekers, it would save time and effort by providing relevant job listings without having to search extensively. For employers, it would ensure that their job postings are being seen by relevant candidates, increasing the likelihood of finding the right fit. Additionally, this personalized job recommendation system could be further enhanced by incorporating data from user's LinkedIn profiles. This would allow for even more personalized job recommendations and also help Glassdoor to expand its user base and reach a wider audience. Overall, the implementation of a personalized job recommendation system would be a valuable addition to Glassdoor's platform and help to attract and retain new users.
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