As employers increasingly rely on pre-hire assessments to screen frontline candidates, a new study from HiringBranch challenges the common practice of reporting soft skills as separate scores. The research, discussed in the latest episode of the podcast You Should Know, indicates that evaluating empathy, acknowledgment, active listening, and reassurance individually yields only moderate correlation with human judgment, while a combined model demonstrates significantly stronger predictive power.
Assaf Bar-Moshe, Chief of Research and Development Officer at HiringBranch, joined host William Tincup on the August 26, 2026 episode titled "Assessing Skills One at a Time Is Costing You Better Hires." Bar-Moshe explained that the company's open-ended, voice-and-writing assessments measure four pillars of customer service: acknowledgment, reassurance through positive language, empathy, and active listening. However, the study found that these skills are interdependent in real customer interactions, and isolating them fails to capture a candidate's true capability.
"If a candidate can express empathy, but is unable to solve the issue correctly or to comprehend the issue correctly or to reassure the customer, then this empathy is nice, but it's actually useless," Bar-Moshe said. This insight stems from HiringBranch's linguistic approach, which Bar-Moshe described as a "sociopragmatic analysis of the words that the candidate is actually saying." Rather than relying on personality-based metrics, the company uses machine learning models trained on years of textual data to predict these skills, then validates them against on-the-job performance months after hire.
The episode also highlighted a real-world example: Tincup recounted a retail confrontation over mispriced broccoli that turned on diplomacy rather than policy. Such scenarios illustrate why hiring managers need assessments that reflect the complexity of live customer interactions, not just isolated traits.
HiringBranch's research shows that calibrations vary by client, industry, and geography. Regional differences across markets like Vancouver, Toronto, and Montreal influence scoring weights for the same role, emphasizing the need for tailored assessments. The company is also developing a self-serve capability that would allow hiring managers to build assessments from a library of conversation flows and skills, reducing reliance on weak or generic job descriptions.
The full study will be available under the AI research tab on the HiringBranch website. This research comes at a time when employers are rethinking how frontline talent—from customer service reps to sales agents to retail associates—is measured against the realities of the job.
For more insights, the episode is available on the You Should Know Podcast page and wherever podcasts are heard.
