Value-Based Pricing sets the price of a product or service based on the value perceived by the customer, rather than on the cost of goods sold
The central idea is that the price should reflect the benefit a buyer derives from the product (time saved, money saved, prestige, performance), which can generate margins significantly higher than those of a traditional cost-plus-margin approach.
A SaaS provider is developing an analytics module that saves its customers an average of €50,000 per year by automating manual reporting
. Rather than charging €200/month for the module (based on its internal costs), it prices it at €1,500 per month, or €18,000 per year: a price that is still well below the value created (€50,000) but that increases its unit revenue by a factor of 7.5
Customers readily accept this because the ROI remains highly positive.
Value-Based Pricing is based on three steps
First, identify customer benefits (cost savings, time savings, increased revenue, emotional value) through qualitative interviews and quantitative studies
Next, measure this value in euros: how many person-days saved, how much additional revenue generated? Finally, capture a fraction of this value (typically 10 to 30%) in the selling price
Pricing analytics tools help correlate the price paid with product features to model perceived value.
This topic is discussed in greater detail in our article on AI pricing in "agentic co-pilot" mode.
Effective use relies on AI-powered pricing in "agentic co-pilot" mode: the system makes suggestions, provides rationale, and issues alerts, while the pricing expert validates decisions that affect KPIs or strategy.

Strategic pricing establishes the profitability framework and long-term brand image, while tactical pricing executes this vision through agile, short-term actions. This alignment protects your margins while allowing you to respond swiftly to inventory levels and competition. A 15% growth target perfectly illustrates this synergy.

The success of a retail pricing strategy relies on moving away from outdated spreadsheets in favor of (semi-)automated execution driven by AI. This technological pivot allows retailers to delicately balance profitability with commercial attractiveness.
This is essential for building customer loyalty, given that 62% of shoppers are willing to switch retailers for a better price.

The success of a pricing project depends not only on the tool, but also on a rigorous methodology that combines data quality with team buy-in. This structured approach allows you to move away from risky manual management and implement automated rules, thereby ensuring long-term profitability and commercial consistency. Talk to a pricing expert (Booper demo).