Predictive Results
Companies that rely on data-driven hiring consistently outperform those using traditional recruitment methods. By integrating predictive sales assessments into their hiring process, leading organizations have transformed how they identify, select, and develop top-performing sales talent. Below are two fundamental examples of real-world experiments that demonstrate the measurable impact of competency-based, predictive hiring—helping clients set clear expectations for what’s possible when science meets sales performance.
1. How HubSpot Built an Outbound Sales Org With Predictive Hiring
Problem As HubSpot scaled, they needed to build a reliable outbound sales engine. But traditional hiring methods risked attracting reps who thrived only with marketing leads, not true hunters.
Solution HubSpot implemented a role-specific sales competency assessment to evaluate hunting ability, consultative selling skills, and coachability, long before interviews. The data helped match candidates to the demands of their outbound model.
Results:
● Built a top-performing outbound sales team.
● Used scores to match reps to roles based on competencies.
● Reduced ramp failure and improved close rates.
● Sales managers had more confidence and clarity during onboarding.
Source: Kurlan & Associates – HubSpot Training Recap
2. How “BigBrains” Went from Random Recruiting to Predictive Success?
In a live field test, three sales teams were formed to sell the same product in the same market. One team was selected using predictive assessment scores, prioritizing Desire, Commitment, and Sales DNA.
Outcome:
● That team made 3x more sales attempts.
● Tied for highest number of deals closed.
● Performed consistently better than the other two teams with more “traditional” selection criteria.
Insights: This experiment validated that core sales competencies like Will to Sell matter more than past experience or product knowledge, especially in high-resistance selling environments.
Source: BigBrains Sales Selection Case Study – Kurlan Blog
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