Management often has an incomplete understanding of salesperson activity, including the quantity and quality of sellers’ interactions with customers and prospects. Many tools attempt to address this gap in management insight: CRM, opportunity pipeline tracking, call recording, and AI based conversational analysis, among many others. This research investigates a range of practices used to improve insight into salesperson activity, identifies best practices among high performing firms, and prioritizes management’s most important improvement opportunities for improving their understanding of buyer/seller interactions.
Condition of Participation
Research participants are asked to complete an online survey lasting approximately 12 minutes, and optionally may elect to participate in a brief telephone follow-up interview.
The study is open to management practitioners responsible for developing, supporting, or managing sales forces; or who are involved with assessing, communicating, implementing, managing, or optimizing sales strategy within their firm. Target participants are involved in executive leadership, strategic planning, sales effectiveness, sales operations, commercial excellence, sales leadership, or sales enablement in organizations with at least US$1 million in annual revenue, or directly employing at least 10 salespeople. Firms or individuals that market technology, products, or services to sales organizations as a core offering are not eligible to participate in this research initiative.
Benefits of Participation
- A copy of the findings report on this research topic
- An invitation to any Sales Management Association webcast in which summary findings are presented to our audience, in July 2022
- An upgraded associate membership in the Sales Management Association for participants who are not already full members of the association.
- Research closes 30 June 2022
- Research report is expected to publish 15 July 2022
Survey results are only reported in aggregate, and never in a way that would compromise the identity of any single respondent. All individual respondent data are treated with strict confidentiality, and will not be distributed.
This research is made possible in part through the underwriting support of Knowme AutoPylot.