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Price and demand-curve Explorer

Explore how customers' willingness-to-pay (WTP) and price-based demand curves affect the optimum price for a product or service. Understand why sales, revenue or profits can have different price optimum points, and so why pricing research helps drive ROI. Our interactive model helps explore how changing demand curves, market size and costs affect price optimisation decisions.

Use pricing research to uncover the underlying demand curve for your markets, layering in deeper details like segments and competitors that can be built into forecast and financial models.

On the chart, drag the points on the demand curve to explore how the optimum points (maxima) for revenue and profit change.

 

Demand is the percentage of customers who would buy at a given price point. By estimating the demand curve with pricing research, the business can calculate potential sales, revenue and profit at different price points in order to optimise pricing.

This pricing model uses a relatively narrow price range - from 75% to 125% of the central Base Price, showing exaggerated changes in demand compared to real world examples, but shows the importance of demand estimation.

Market size - the number of customers, units bought, and base price can all be adjusted which will change the totals, but not the shape of the curves.

Adjusting the unit cost (given as a a percentage of the central base price) will shift the profit curve. Increasing unit cost (and so decreasing margin per unit) implies more sales are needed for the same profitability. Low unit cost - and so high margin - aligns profitability more to the revenue curve.

Included are some text book demand curves. These are not common in real pricing research. Real world demand curves have varying slopes and kink points due to price thresholds, and segmentation effects. Different curve shapes lead to different pricing decisions, and show the importance of estimating specific demand curves for specific products.

(For economics students note the price is on the x-axis. In textbook econmics, price is commonly on the y-axis, as output is what is being chosen. Here we want to choose optimum price points)

Classically, the demand curve can lead to different optimum prices for sales, revenue and profit (triple point outcome). Start ups often aim for sales maximisation, then as the product matures and customers habits bed in, pricing moves towards profit optimisation. A common private equity buy-out strategy is to take a company moving out of start-up phase with retained customers to move prices to the right to increase profitabilty and ROI.

This pricing model is relatively simple for illustration - one product, no competitor effects, and no segmentation, assuming all customers buy the same volume and that volume doesn't vary by price, and costs don't change by volume. Similarly there are no marketing impact or distribution elements. However, this type of model helps in understanding core dynamics that affect ROI, and can be extended to more complete estimates for real projects with full pricing research and pricing studies.

If you enjoy this Pricing Explorer, also take a look at our Conjoint Explorer to see how Conjoint Analysis can be used for pricing research, or try our Conjoint Analysis Demonstration. Conjoint analysis is one of the key research tools for understanding price sensitivity.

We offer a full range of research and consultancy services around approaches to pricing and can help guide you through the sensitive questions about finding out what customers value, and what they are willing to pay for.

  • Also check out our Conjoint Explorer to understand how estimates of market demand can be made using conjoint analysis

For help and advice on carrying out pricing research and setting pricing strategies contact info@dobney.com


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