Wealth management firms charging a flat fee on assets are not incentivized to build sophisticated alternative investment teams. It's easier and more profitable to use basic stocks and bonds, as building an alternatives practice is expensive, complex, and doesn't increase their fee.

Deliver's growth stagnated until they shifted from complex, variable fees to a simple flat rate. This treated pricing not as a billing model but as a product feature that solved the customer's core need for financial predictability, which became their primary growth catalyst.

In an era of information transparency, having different prices for different customers based on negotiation skill destroys reputation. The price should be consistent, with flexibility offered through four core business levers (volume, payment speed, commitment length, deal timing), not arbitrary discounts.

Ledge's pricing scales with a customer's operational complexity (entities, currencies, channels), not user count. This aligns their revenue with the value of their AI automation, which aims to make finance teams leaner. It's a strategic bet that value comes from efficiency gains, not headcount.

The standard percentage-based AUM fee is fundamentally misaligned with the value provided, especially when advisors simply use index funds. It persists not because of its fairness, but because fees are deducted directly and invisibly from accounts, obfuscating the true cost from the client.

Exposing the enormous fees paid to external managers forces asset owner boards to ask, "Is there another way?" This transparency is the key driver that prompts them to consider the strategic benefits of building internal investment teams.

Effective pricing is not just a number; it is a value story. The ultimate test is whether a customer can accurately pitch your product's pricing and value proposition to someone else. This reframes pricing from a simple number to a compelling narrative.

AI SaaS companies have variable, usage-based costs, but customers demand predictable flat fees for procurement. Product Fruits found charging per usage failed. The solution is to accept the uncertainty, create flat-fee plans, and absorb the risk of variable backend costs to close deals.

To combat the unpredictable costs of token-based AI usage, Pega is adopting a value-based pricing model. Instead of charging per token, they charge based on work completed (e.g., per loan funded or service request processed), aligning costs directly with business outcomes and enabling forecasting.