Beyond the Retention - Acquisition Trade-Off: Capabilities of Ambidextrous Sales Organizations

Edwin J. Nijssen, Paolo Guenzi, Michel Van der Borgh

Research output: Contribution to journalJournal articleResearchpeer-review

Abstract

Sales organizations aim to grow their firms' business by acquiring new customers while retaining their existing ones. Although customer acquisition and retention are complementary processes, they involve different sales process capabilities that often compete for investments. However, firms that succeed in effectively combining these capabilities are “ambidextrous” and will enjoy superior growth and profits. Although developing ambidexterity is a fundamental sales management task, it has received little attention in research. Based on the Motivation-Opportunity-Ability framework we identify a set of organizational sales capabilities that can help sales organizations' joint management of acquisition and retention capabilities, and explain their influence drawing on Job Demands-Resources (JD-R) theory. Survey and time-lagged archival performance data from 174 firms provide an empirical test of the conceptual model and hypotheses developed. Results confirm that incentive management, cross functional cooperation, and the interaction of cross functional cooperation and sales training capabilities are positively correlated with sales organization ambidexterity. In addition, we find a positive correlation of customer prioritization on ambidextrous selling. Results confirm that firms with high levels and aligned acquisition and retention capabilities enjoy superior organic growth. However, contrary to expectation, increases in profit growth are only accomplished if acquisition capabilities are high.
Original languageEnglish
JournalIndustrial Marketing Management
Volume64
Pages (from-to)1-13
Number of pages13
ISSN0019-8501
DOIs
Publication statusPublished - Jul 2017
Externally publishedYes

Keywords

  • Sales capabilities
  • Acquisition
  • Retention
  • Ambidexterity
  • Sales performance
  • Polynomial regression

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