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Operationalizing salesperson performance with secondary data: aligning practice, scholarship, and theory

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Abstract

Despite the large body of research that examines the determinants of salesperson performance, significant variation exists regarding how scholars can operationalize salesperson performance using secondary, firm-provided data. Moreover, this variation often exists without explanation or justification. We explore the issue in three parts. First, we conduct practitioner surveys to discover various salesperson performance operationalizations (SPOs) in use by salespeople and sales managers. Second, using a carefully constructed and theoretically driven evaluative framework, we conduct a systematic review of the literature on salesperson performance that encompasses over thirty years of empirical research on the subject; this review allows us to better understand the SPOs that scholars use. Third, we compare these practitioner and scholarly perspectives to create a comprehensive conceptual model of the different types of SPOs. The model highlights theoretical insights and provides guidance to scholars and reviewers related to the selection of appropriate SPOs for meeting specific research objectives.

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Notes

  1. Although our focus here is on secondary data, we recognize that measures of salesperson performance using primary data are available. In these cases, performance is assessed via surveys and often is self-, manager-, or customer-reported. The most popular scale is sourced from Behrman and Perreault (1982). See Web Appendix C for details.

  2. We conducted preliminary interviews with 25 sales professionals and leaders prior to creating our practitioner survey. These interviews were used to verify how practitioners view salesperson performance and to reinforce the validity of the categories identified in the conceptual background section. For more details, see Web Appendix A.

  3. We determined high importance by the percentage of individuals who selected “Very Important”, or a 5 on our survey. This decision was based on the logic that scholars are likely to focus on only one dependent variable from each SPO category (e.g., a scholar is not likely to model revenue alongside sales units).

  4. While we exclude research using primary data from our formal review of the literature on secondary salesperson performance, we provide a table that lists and denotes characteristics (e.g., what scale was used, source of rating) of primary salesperson performance studies in the Web Appendix C for interested readers.

  5. In one notable example of an article that provides a strong theoretical rationale for its SPO, Hohenberg and Homburg (2019) clearly define performance as it relates to innovation sales success, established-solution sales success, and sales-unit revenue.

  6. Of note, issues with quota setting may be amplified when using repeated-measures data because the quota itself could change over time, rendering the resulting variable nearly impossible to interpret. In other words, is the SPO changing because the numerator or denominator (e.g., “sales/quota”) used in its calculation has changed? Care should be taken to establish and communicate the denominator’s stability in these situations.

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Acknowledgement

We gratefully acknowledge the generous support awarded by the American Marketing Association Sales SIG Global Database Initiative.

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  1. College of Business, Florida State University, 821 Academic Way, Tallahassee, FL, 32306-1110, USA

    Willy Bolander, Alec Pappas & Daniel R. Bradbury

  2. E.J. Ourso College of Business. Louisiana State University, 501 South Quad Drive, Baton Rouge, LA, 70803, USA

    Nawar N. Chaker

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Bolander, W., Chaker, N.N., Pappas, A. et al. Operationalizing salesperson performance with secondary data: aligning practice, scholarship, and theory. J. of the Acad. Mark. Sci. 49, 462–481 (2021). https://doi.org/10.1007/s11747-020-00752-0

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