Paycom Retention Dashboard
LeaderOur truly single HR and payroll software automates the routine to simplify life for employees and transform businesses.
Est 1998|Valuation $10.8B|Raised $3.6B
Published May 16, 2026
Public materials for the Retention Dashboard do not include independent, quantified case studies demonstrating measured reduction in attrition or validated prediction accuracy.
The vendor publishes retention-related educational content (guides and blog posts) on retention strategies and onboarding. These resources are educational but should not be interpreted as independent proof of the feature’s effectiveness.
Recommendation for procurement: Request customer references specifically using the Retention Dashboard, pre/post turnover metrics with a defined methodology, and the opportunity for a pilot with measurable outcomes.
Based on review patterns and analyst positioning, a common fit is organizations ranging from small to mid-sized, with some customers outside this range.
Observed examples in user reviews and case references include retail, consumer goods, travel and hospitality, and segments of healthcare.
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Download full report →Across major review platforms, the broader Paycom suite is frequently described positively for:
Examples of reviewer sentiment (paraphrased):
Common areas of criticism in user reviews and community posts for the Paycom suite include:
Note: Most public reviews address Paycom’s overall suite rather than the Retention Dashboard specifically. Organizations should obtain references from customers actively using the Retention Dashboard to understand real-world accuracy, frequency of useful alerts, and operational impact.
Paycom Retention Dashboard is an analytics feature within the Paycom HCM suite intended to help employers identify employees at higher risk of leaving and visualize turnover/retention trends. The vendor describes the feature as providing retention scores for each W‑2 employee derived from a proprietary algorithm that uses multiple employee data points; scores are reported to update as underlying employee data changes.
Key functions (vendor-described):
Important caveat: Public vendor materials do not disclose the model methodology, validation statistics (for example, precision/recall or false positive rate), bias testing, or ongoing monitoring processes. Organizations should treat the term "predictive" as a vendor claim that requires verification and internal validation before operational use.