How to Hire Great Pricing People
Getting the Right People in the Right Places to Generate the Results You Want
While the pricing practice has certainly grown, it's still very difficult to find people who already possess the exact skillsets your pricing team needs. So, how do you identify the candidates with the raw materials to be most successful? How do you ensure that you're putting the right people in the right places? What should you be thinking about as you expand and develop your pricing team? In this on-demand webinar, you'll learn about:
- The 7 most important attributes you should be looking for, regardless of the specific pricing role or function.
- The pros and cons associated with hiring internal candidates or bringing people in from outside your company.
- The 3 technical pricing concepts that are huge differentiators for any candidate you might be considering.
- A variety of strategies and tactics for getting beyond the resumes to assess candidates' real capabilities.
This webinar is just one of hundreds of educational resources you get access to as a PricingBrew Journal subscriber.
More Subscriber-Only Resources From Our Library
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Stop Living With Subpar Price Execution!
In this Expert Interview, Cath Brands of Flintfox discusses what pricing teams can do to finally address those frustrating and costly price execution issues that have been slowing us down and holding us back.
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Boosting the Pricing Team's Influence
How can a B2B pricing team improve results when they don't control all the cooks in the kitchen? How can they be heard when others don't have to listen? In this session, learn the science of influence and persuasion.
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5 Pricing Trends You Can't Afford to Ignore
From our unique vantage point, we've identified a number of larger trends that pricing teams need to be prepared for. In this on-demand webinar, we explore five of these trends and discuss the implications and ramifications.
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Working With "Bad" Pricing Data
In B2B, there are so many moving parts that always having a perfectly accurate and complete dataset just isn't very realistic. So we've got to figure out how to do the best we can with the data we've got.
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