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Highlights
Welcome to another episode of Category Visionaries — the show that explores GTM stories from tech’s most innovative B2B founders. In today’s episode, we’re speaking with Stephen Johnston, CEO and founder of GoodJob, an AI recruiting platform that has raised $9 million in funding.
- Stephen’s journey as a serial entrepreneur, from his first tech company in the smart grid space to his current venture, GoodJob, and his passion for building companies from scratch.
- The problem of bad hires costing businesses dearly, both financially and in terms of missed opportunities, and Stephen’s mission to increase the probability of hiring the right person from 50% to 75-85%.
- GoodJob’s unique approach to building predictive behavioral models based on a company’s existing employee data, ensuring a customized solution that accounts for cultural fit and role-specific success factors.
- The platform’s ability to identify employees who may be in the wrong role and suggest better-fitting positions within the company, enabling internal mobility and reducing turnover.
- GoodJob’s early traction with enterprise customers, including a large healthcare system in Mississippi and a state-funded pilot program involving major employers like Continental Tire and Nissan.
- The advantages and challenges of building a tech startup in the South, and Stephen’s experience leveraging remote work to attract top talent from around the world.
- Stephen’s perspective on the importance of focusing on a specific customer profile while remaining open to pivots based on market feedback and evolving needs.
Actionable
Takeaways
Solve Real Problems, Not Symptoms:
In his research, Stephen found that most HR tech was designed to help companies cope with the problem of bad hires, rather than actually solving it. By digging deeper to understand the root cause - a lack of trait and behavioral data early in the hiring process - GoodJob was able to develop a truly innovative solution. Founders should strive to identify and address the underlying issues driving customer pain points, not just treat the symptoms.
Customize Your Solution to Each Customer's Unique Context:
GoodJob's predictive models are built using data from a company's existing employees, ensuring that the platform captures the specific behaviors and cultural attributes that drive success in that particular organization. By tailoring your solution to each customer's unique environment, you can deliver more accurate and impactful results than a one-size-fits-all approach. Founders should seek ways to incorporate customer-specific data and insights into their offerings.
Leverage Partnerships to Drive Early Adoption and Credibility:
GoodJob's partnerships with the state of Mississippi and the Society for Human Resource Management (SHRM) were instrumental in landing early enterprise customers and establishing the startup's reputation in the industry. By aligning with trusted institutions and participating in pilot programs, founders can access valuable opportunities to prove their solution's value and build a track record of success.
Embrace Remote Work to Tap Into Global Talent Pools:
Having learned the limitations of geographically constrained hiring in his previous venture, Stephen intentionally built GoodJob as a remote-first company from day one. This approach enabled him to attract top talent from around the world, rather than being limited to the local market. Founders should consider how a remote or hybrid model can expand their access to specialized skills and diverse perspectives.
Focus on Your Ideal Customer Profile, But Remain Agile:
While Stephen advocates for a focused go-to-market strategy targeting a specific customer profile, he also emphasizes the importance of staying open to pivots based on market feedback and evolving needs. By striking a balance between focus and flexibility, founders can efficiently validate their assumptions while remaining responsive to new opportunities and insights.
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