Sales Experience Quality Benchmark Report

Executive Summary

Sales and Marketing have long been convenient scapegoats for one another. When one fails to perform, the finger of blame is often pointed at the other. Observers of the marketing and sales processes in any organization are usually quick to determine that when there is failure to perform, rarely is just one of these entities wholly at fault. And yet the Blame Game persists.

What isn’t disputed is that in B2B sales and marketing organizations, the individual sales representative is the focal point of sales interactions with clients. When a field sales rep walks into a meeting with a client or prospect, the success of that interaction rests of the shoulders of that sales rep. When the rep performs well, the chance for revenue increases. But when the rep doesn’t perform well in a sales meeting, regardless of the reason, the chance for revenue is jeopardized.

In a study sponsored by Showpad, Demand Metric conducted a survey to explore the impact of a “bad” sales interaction, whereby a “bad” interaction signifies a poor performing sales conversation that excludes a vendor from consideration. The purpose of this study is not to treat sales reps as scapegoats, but to determine how sales opportunities are affected by bad sales meetings, and hopefully gain insights about how to prevent bad meetings.

These insights can help the marketing and sales functions understand how to better collaborate to ensure the highest possible incidence of sales meetings with favorable outcomes.

Table of Contents

1. Introduction
2. Executive Summary
3. The Sales Process
4. Sales Performance
5. "Bad" Sales Meetings
6. Marketing Performance
7. Turning the Tables
8. Analyst Bottom Line
9. Acknowledgements

10. About Showpad
11. About Demand Metric
12. Appendix - Survey Background

Research Methodology

This Demand Metric Sales Interaction Quality Benchmark Study survey was administered online during the period of June 19, 2014 through July 9, 2014. During this period, 247 responses were collected, 182 of which were complete enough for inclusion in the analysis. The data was analyzed using SPSS to ensure the statistical validity of the findings.