Fee Elasticity Analyzer
Understand your clients' price sensitivity
Model how a fee increase or restructure impacts client retention probability.
Powered by intelligence from 23,428+ SEC-registered RIA firms
The Problem This Solves
You suspect your fees are below where they should be, but you've never raised them because you can't predict which clients would walk. So you leave revenue on the table year after year, financing your own underpricing out of fear of an attrition wave you can't model.
✦ You'll know the exact fee increase point — typically 8–15% — that maximizes net revenue, and which client tiers will absorb it without leaving.
Tool Details
How It Works
Models revenue impact of fee changes using price elasticity analysis calibrated against advisor-client behavior patterns. Client retention probability at each fee level uses a logistic decay function — retention decreases slowly below 10% increases and accelerates above 20%. Net revenue impact is the product of the new fee level and expected retained client base. The optimal fee increase point maximizes expected revenue, typically 8–15% for practices with strong relationships and high recurring revenue. Segmentation analysis identifies which client tiers have the highest fee tolerance.
Data Sources
- •Price elasticity model calibrated against Synseus aggregate data
- •Client retention probability curves from RIA industry research
- •Fee benchmarks from SEC ADV Part 2 public filings
Audit Parameters
- •Model: Logistic decay retention curve
- •Benchmark: Synseus aggregate by AUM tier
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