Impact Over Input: The Shift to Outcome-Based Remuneration
A mediasense report exploring the future of outcome-based agency remuneration, and how AI, data and measurement are reshaping the model.
As marketing leaders face increasing pressure to prove value, many are questioning whether traditional agency remuneration models are fit for purpose. This report explores the growing interest in outcome-based remuneration (OBR), the barriers to adoption, and how AI, data and measurement are reshaping the conversation.
Key Takeaways
- 85% of respondents expect outcome-based remuneration to grow, signalling increasing momentum across the industry.
- 81% believe outcome-based models can strengthen client-agency relationships through greater alignment and shared accountability.
- 69% cite attribution challenges as a major barrier to adoption, highlighting the continued need for better measurement and data access.
- Most respondents believe AI will accelerate the shift from input-based to outcome-based remuneration, changing how agency value is defined and rewarded.
Report Highlights
What’s Driving the Shift to OBR?
The market forces, commercial pressures and technological advances that are changing how agencies are rewarded.
What’s Holding Adoption Back?
The practical challenges around data, attribution, governance and organisational alignment that continue to limit wider adoption.
How Is AI Changing Agency Economics?
Why automation is challenging traditional time-based remuneration models and accelerating the focus on value creation.
What Does the Future Look Like?
Why hybrid remuneration models are expected to remain the preferred approach for many advertisers and agencies.
Download Impact Over Input: The Shift to Outcome-Based Remuneration for the latest research, industry perspectives and practical guidance on designing more effective advertiser-agency compensation models.
Produced by mediasense in collaboration with the World Federation of Advertisers (WFA) and Meta.
For further insights on this topic, read our latest blog (by Adam Edelshain), here.
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