C · Sales process & closingExternally proven

Sales Acceleration Formula

Mark Roberge's approach of treating sales scaling as an engineering discipline, its best-known component is empirical hiring scoring on coachability, curiosity, prior success, intelligence, and work ethic.

When you need this method

Your sales team is growing, but every hire is a gamble: some new reps perform, others don't, and no one can tell in advance which. Training and evaluation depend on individual managers rather than a repeatable system. The result is costly mis-hires and a sales organization that cannot be scaled predictably.

Approach

  1. 1Define a hiring scoring model, starting criteria: coachability, curiosity, prior success, intelligence, work ethic and rate every candidate against it.
  2. 2After each cohort, test which criteria actually correlate with later performance and adjust the weights.
  3. 3Standardize training instead of having new reps shadow others: same content, same assessments, measurable learning goals.
  4. 4Manage performance quantitatively: the same metrics for everyone, variances made visible, coaching aligned to them.

Typical application

A typical case: a growing B2B SaaS company hires several AEs within a year, each based on interview impressions. Performance varies widely and the reasons stay unclear. The company introduces a simple score across the five criteria, documents every hire, and after two quarters compares scores against quota attainment. Coachability and demonstrated prior success turn out to be the strongest signals, future interviews are structured around exactly those traits.

Limits and counter-indications

The model needs enough hires to test criteria empirically, at two hires a year it remains structured gut feel. The original weighting comes from a specific context (HubSpot, inside sales) and does not transfer unexamined. It addresses hiring and ramp-up, not whether positioning and offer hold up.

How to measure impact

Correlation between hiring score and later quota attainment per cohort; alongside it, ramp time to full productivity and the spread of performance across the team.

Related methods

Tools for this

Sources

  1. 1.Verbeke, Dietz, Verwaal: Drivers of sales performance, a contemporary meta-analysis, Journal of the Academy of Marketing Science 39, 2011 (opens in a new tab) · Journal of the Academy of Marketing Science (Springer, Open Access) · 2011 · academic and scholarly literature · supports the underlying mechanismShows that sales performance is associated with measurable characteristics of salespeople: across studies from 1982 to 2008, the meta-analysis finds the strongest associations for selling-related knowledge (beta = .28), adaptiveness (beta = .27), role clarity (beta = -.25 for role ambiguity), cognitive aptitude (beta = .23) and work engagement (beta = .23). The strongest drivers can themselves be trained and organised, so the meta-analysis supports managing sales performance against measurable factors rather than selecting hires against the five criteria.
  2. 2.Mark Roberge: The Sales Acceleration Formula, Wiley, 2015 (opens in a new tab) · Wiley · 2015 · practitioner source · describes the methodConfirms the author, the February 2015 publication date and ISBN 978-1-119-04707-0 of the book in which the method is set out. The scoring model and the five hiring criteria are in the book itself, not on the publisher's page.

Origin: Roberge

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