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How to Use Data to Hire Better Salespeople

By December 15, 2016August 13th, 2017Inbound Marketing

You could say that HubSpot wrote the book on software sales training. The company’s Chief Revenue Officer Mark Roberge wrote one, called The Sales Acceleration Formula. In the book, Mark documents how he used data to come up with a solid predictor of a salesperson’s potential and performance.

Top 5 Super Traits

After all this analysis, Roberge and his team extracted five qualities that they believe, based on their data, predict success in any sales organization. We’ll call these Super Traits:

  1. Coachability
  2. Curiosity
  3. Prior Success
  4. Intelligence
  5. Passion

Mark measures coachability by how candidates respond to critical feedback. Curiosity is important because good salespeople ask a lot of questions to truly understand a customer’s needs. Prior success, as mentioned, means having achieved excellence in some capacity. He measures intelligence by how quickly someone can grasp and articulate a new concept. Passion can be seen by the pleasure and pride someone takes in his or her work.

14 Categories That Indicate Success

Mark eventually broke those top five super traits down to 14 characteristics of a successful salesperson at HubSpot. He then weighted each characteristic based on its correlation to real world success over time. Finally, he used these characteristics in the interviewing and hiring process, ranking candidates on their performance in each area.

The characteristics are:

  1. Knowledge of HubSpot
  2. Internet Marketing Experience
  3. Brevity
  4. Adaptability
  5. Prior Success
  6. Initiative/Passion
  7. Needs Identification
  8. Rapport Building
  9. Voice Quality
  10. Intelligence
  11. Convincing
  12. Technical Aptitude
  13. Objection Handling
  14. Closing Ability

Predictive Hiring Practices

These are the most important characteristics that Roberge found predictive of success at selling HubSpot’s marketing automation products. In addition to using these characteristics as hiring criteria, he also used them for performance evaluations after six months on the job. The data from the performance evaluations was used to sharpen the correlation figures over time as the data grew.

One thing you don’t see on the list is industry experience. HubSpot didn’t find a strong correlation between past SaaS sales experience, or even past sales success. Roberge found that success in any previous endeavor–whether educational, athletic or occupational, correlated to success at HubSpot.

New Kind of Sales Needs New Kind of Hiring

Roberge’s success characteristics reflect the fact that the relationship between sales and customers has fundamentally changed in the digital age. Customers can gather vast amounts of information before contacting a company to discuss a solution. They are typically coming because they have a problem that they can’t solve by themselves. The salesperson’s charge is to understand the customer’s problem and to help determine the best way to solve–even if it means a different solution than the one you are selling.

While the characteristics that Mark measures are very human and soft, the means of measuring are hard science, and it is continuously being improved. His team conducted some 1,000 interviews to hire about 60 people when he began this hiring process. They graded each candidate during the interviews and again six months later,  and ran a regression analysis of how high or low scores in particular areas correlated with success. They used the results to redesign the sales interview with an updated set of criteria and score sheet to better identify the best candidates.

Roberge and his team built a sales hiring and training automation system akin to the HubSpot marketing automation platform–a system that gathers and tracks key characteristics that lead to desired results. He built the HubSpot sales team into a $100 million revenue generator in just seven years.

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