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Improving Candidate Engagement and Reducing Dropout in Recruitment Process

Authors: Anand Kumar D; Dr. Neena PC;

Improving Candidate Engagement and Reducing Dropout in Recruitment Process

Abstract

India’s EdTech and skill development sector has rapidly expanded due to rising demand for employability programs, digital learning platforms, and corporate training partnerships. However, talent acquisition in this industry continues to face critical challenges, particularly in sustaining candidate engagement and reducing dropout across recruitment stages. This case examines the recruitment inefficiencies observed at Ethnus Consultancy Services Pvt. Ltd., where low response rates, unclear communication, manual follow-up processes, and inconsistent tracking led to high levels of candidate disengagement. Through strategic interventions—such as shifting sourcing channels toward college placement cells and recruitment vendors, standardizing communication templates, implementing structured follow-up reminders, and adopting centralized Google Sheets trackers—the internship led to a significant improvement in response rates, interview attendance, and overall placement outcomes. The case highlights how streamlined communication, targeted sourcing, and basic process automation can substantially enhance recruitment efficiency in high-volume EdTech hiring environments. Insights from this experience align with academic frameworks on recruitment funnel optimization, candidate experience management, and HR operational efficiency in skill development industries.

Keywords

Recruitment dropout, Talent acquisition, EdTech hiring, HR operations, Candidate engagement

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    popularity
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    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green