Fee Elasticity Analyzer
Explore how fee changes affect retention, on sample client segments
Model how a fee increase changes expected churn and net revenue for a client segment. Segments are sample data in demo mode; entering your own is not available yet.
The Problem This Solves
✦ You'll model how a fee increase moves expected churn and net revenue across sample client segments.
Tool Details
How It Works
Models revenue impact of fee changes using a fixed price-elasticity coefficient for each client segment. Expected churn from a fee increase is linear: the segment's elasticity coefficient times the size of the increase, capped at 50% of clients; a fee decrease adds no churn. Net revenue impact is the product of the new fee level and expected retained client base. The optimal fee change is the tested step (from -20% to +30% in 5-point steps) with the highest net revenue. Segmentation analysis identifies which client tiers have the highest fee tolerance.
Data Sources
- •Price elasticity coefficient per client segment (fixed sample values; not calibrated against any dataset)
- •Linear churn model: expected churn = elasticity coefficient x fee increase, capped at 50%
- •Segment fees, client counts and average AUM (sample data in demo mode; no fee benchmark is read)
Audit Parameters
- •Model: linear churn, capped at 50%
- •Benchmark: none (fixed sample elasticity coefficients)
Related Tools in Pricing & Fees
Ready to use Fee Elasticity Analyzer?
Built exclusively for independent RIAs and advisory firms ready to grow, protect, and scale their practice.
Start Your 14-Day Free Trial