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Research / Using Incentives to Drive Pipeline - Methodology
by Incentive Research Foundation
This report synthesizes findings from 10 in-depth semi-structured interviews conducted between August 2025 and January 2026 with channel incentive program experts across multiple industries and roles.
Scope note: This research focuses primarily on ongoing, long-term (often annual) channel incentive programs and benchmarking-style designs, rather than one-off short-term “spiffs.” Short-term programs can still apply these principles, but measurement approaches and partner relationship dynamics can differ.
Min Choi, Germania Insurance
Rachel McInnis, Maritz
Interviews explored program design principles, ROI measurement approaches, success factors, and challenges. Participants shared specific program examples, budget structures, measurement methodologies, and lessons learned from both successful and struggling programs. Key themes were identified through thematic analysis of interview transcripts, with cross-validation across multiple participants to ensure findings reflected industry patterns rather than individual perspectives.
Sample skewed toward larger organizations and established programs; emerging program challenges may be underrepresented
The content in this report is the product of the contributions of seasoned experts in incentive program design paired with AI’s ability to process massive amounts of knowledge in mere minutes.
A thorough review of literature published between 2000 and 2026, in-depth interviews with 10 incentive industry veterans with backgrounds in B2B channel programs, and deep experience from my co-authors (two among the most respected incentives professionals in the industry, and another, a leading academic researcher in the field) provided the enormous human contribution to this paper.
Given the breadth of the resources at my disposal, I created an AI Researcher Agent to gain leverage over the data. Instead of spending at least two full weeks reading hundreds of pages of related reports and articles, coding more than 100 pages of interview transcripts and then synthesizing it into a first draft – as I would have just months ago – I used my agent to find and analyze dozens of high-quality reports, journal articles, and industry pieces alongside the interview transcripts. It synthesized and referenced the findings in minutes, allowing me to focus on the implications of the data rather than finding, organizing, reading, highlighting, and re-reading it.
This fed into The Draftsman Agent, which I used to execute the vision. I acted as the architect, defining the arc of each section then iterating each draft with my co-authors who provided extensive feedback that I fed back into the model for synthesis, ensuring that every output was grounded in the knowledge and experience of human experts.
To help visualize the work, I asked the AI agent to build tables that would provide efficient references for readers and break up the text. I also asked it to construct mini-case studies from the interviews, then present them succinctly. I acted as the Creative Director, refining the prompts until the tables and case studies matched the concepts. My co-authors flagged passages that seemed more machine than human and we rewrote them. Finally, I used Claude Code in terminal mode (on my computer) to build an interactive companion tool for this paper, so that readers pressed for time could either use it to augment the paper or even to skip the paper altogether.
Throughout this process, I applied my human judgment as Editor-in-Chief. While the machine provided the speed, my co-authors and I provided the standard. Every sentence was reviewed, refined, and often rewritten to ensure it carried nuance that no machine can simulate.
The following bibliography covers external research highly relevant to channel incentive programs, published between 2020–2026 from credible academic and industry sources, organized by topic area.
Incentive Research Foundation (IRF). (2025). Top 10 Things Top Performing Companies Do Differently: 2025 Top Performers Study. https://theirf.org/research_post/top-10-things-top-performing-companies-do-differently/
Incentive Research Foundation & SITE. (2025). Incentive Travel Index 2025. https://www.incentiveindex.com/
Canalys. (2024). Channel Incentive Management (CIM) Platform Analysis. https://canalys.com/insights/channel-incentive-strategies-revamp
Using Incentives to Drive Pipeline explores what makes channel incentive programs effective, showing why they must compete for partner mindshare, reward behaviors across the full sales pipeline, and function as long‑term partnership investments—not just transaction‑based incentives.
Our panel shared key findings from the 2026 European Top Performers Study, examining how leading organizations across Europe design and manage incentive travel programs to drive engagement, performance, and measurable business outcomes.
