Retaining and growing talent through skills-based hiring: Insights from Eightfold AI’s match score

In this blog, we analyze promotion and retentionutcomes for employees hired with different Eightfold AI Match Score ranges.
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Retaining and growing talent through skills-based hiring: Insights from Eightfold AI’s match score

5 min read

Hiring and retaining great talent has become one of the hardest and most expensive challenges for organizations today. Resumes and degrees tell you what someone has done, but not necessarily what they can do. That’s why skills-based hiring is critical: it identifies candidates on the basis of ability, not proxies.

Eightfold Match Score provides a quantitative signal of skills alignment. In this blog, we analyze promotion and retention outcomes for employees hired with different Match Score ranges. Using retention analysis and promotion-rate tracking across organizations and industries, we find consistent evidence that higher Match Scores predict significant long-term outcomes.

Methods:

Our analysis used aggregated, anonymized hiring and career progression data across multiple organizations. We compared outcomes for employees with high Match Scores (≥4.0) against those with lower scores. Key measures included:

  • Promotions: cumulative promotions per capita by hire date. The study consists of approximately 688k employees covering the years 2021-2025.
  • Retention: survival rates and Kaplan-Meier curves to capture attrition risk over time, by hire date. The study consists of approximately 377k employees covering the years 2023-2024, and undersampling the retail industry.
  • Retail Industry Segmentation: high-churn sectors such as retail. The study consists of approximately 209k employees covering the years 2023-2024.

Results:

  • Hire the Strongest Talent: High Match Score hires (≥4.0) are promoted at higher rates. Within 2 years of hire, the high Match Score group experienced nearly 50% more promotions (per capita) than the low-match group. In other words, skills-based hiring using Eightfold’s Match Score yields significantly higher performing talent. 
  • Higher Retention: Candidates identified as strong matches (Eightfold Match Score ≥4.0) had an overall 12-month retention rate of ~78%, higher than the 73% retention rate for lower-score hires. This ~5% gap yields a large turnover cost-savings for any organization adopting Eightfold’s Match Score. The effect is even more pronounced for mass-hiring organizations such as those in the retail industry: a 12.5% increase in 12-month retention in high Match Score hires.
  • Turnover Cost Savings: Even modest improvements in retention translate into major savings. Using Match Scores to prioritize high-fit candidates could improve overall retention by ~1%, which for a 10,000-employee company would avoid an estimated $5 million in annual turnover costs. For a smaller 2,000-employee company, the savings would be $1 million in annual costs saved.

Promotions and career growth distribution (All organizations)

High Match Score hires (≥4.0) are promoted at higher rates. Within two years of hire, the high Match Score group experienced nearly 50% more promotions (per capita) than the low-match group. Promotions are one of the strongest and most direct indicators of internal employee performance.

Cumulative promotions over time by Match Score group

Cumulative promotions over time by Match Score group
Cumulative promotions over time by Match Score group. This chart tracks the average number of promotions per employee (“cumulative % of group promoted”) since hire for high Match Score hires (≥4.0) versus low Match Score hires. Higher Match Score employees succeed more in their roles, yielding ~40–50% more promotions than the low score buckets.

Promotion rate difference (high vs. low Match Score groups)

Promotion rate difference (high vs. low Match Score groups)
Percent of promotion rate difference (high minus low Match Score groups). This curve shows the relative % gap in cumulative promotions between the groups over time. The promotion advantage for high-match hires hovers around 40–50% higher throughout the observed period, indicating a consistent and early significant lift of high-performing talent in the organization.

Retention outcomes (All organizations)

Candidates with strong matches (Match Score ≥4.0) had an overall 12-month retention rate of ~78%, compared to 73% for lower-score hires. This ~5% gap yields meaningful turnover savings.

Kaplan–Meier retention curves by Match Score group

Kaplan–Meier retention curves by Match Score group
Retention curves by Match Score group (Eightfold-wide analysis). Each curve shows the percentage of employees still employed over time since their hire date, for high Match Score hires (Score ≥4.0, blue line) versus lower Match Score hires (Score <4.0, orange line). Higher Match Score employees have consistently better retention over time.

Retention rate difference over time (high vs. low Match Score hires)

Retention rate difference over time (high vs. low Match Score hires)
Retention rate difference over time between high vs. low Match Score hires. This plot shows the percentage-point gap in retention (high-match minus low-match) at each tenure duration. The retention advantage for high-match employees emerges quickly (reaching > 6% at the peak, nearly 90 days into the position) and remains sustained through day 500.

Industry case: Retail

In retail, a high-churn sector, retention improvements are even more pronounced. At ~120 days, the retention gap reached ~18% (72% vs. 54%).

Kaplan–Meier retention in retail hires by Match Score group

Kaplan–Meier retention in retail hires by Match Score group
Kaplan-Meier retention in Retail industry hires, by Match Score group. Even in this high-churn sector, employees hired with Match Score ≥4.0 (blue) show significantly higher retention rates in the first year than those with lower scores (orange). Notably, at ~120 days (4 months), the retention gap is around 18% in relative terms (e.g., 72% vs 54% retained) in the high vs low score buckets.

Retention rate difference over time in retail hires

Retention rate difference over time in retail hires
Retention rate difference over time between high vs. low Match Score hires for Retail Industry hires. This plot illustrates the gap between high and low Match Score employees in the retail industry, highlighting a significant difference in tenure between the two groups, which reaches a maximum at around 100 days into a new position.

These findings demonstrate that Match Score is a robust predictor of both retention and promotion outcomes.

Key observations:

  • The correlation between Match Score and career growth appears consistent across organizations.
  • The early divergence in retention curves indicates that skills alignment predicts not only long-term engagement but also short-term success in role fit.
  • The effect is generalizable across industries, and is stronger in higher-turnover industries such as retail.

Limitations

This analysis measures relative outcomes within Eightfold’s dataset. While effects are strong and consistent, outcomes may vary depending on organization size, industry, and implementation of skills-based hiring practices.

Conclusion and implications

Our analysis shows that Match Score provides a measurable and reliable signal for hiring outcomes. Employees hired with higher Match Scores are more likely to stay longer, advance faster, and contribute greater value to their organizations.

For technical practitioners, these results validate the use of skills-based models and survival analysis in predicting workforce outcomes. Organizations underscore the importance of adopting data-driven approaches to hiring.

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