Average Margin Can Hide Pricing Problems
Sales analysis often starts with revenue, volume, and average margin. The problem is that aggregated figures can conceal very different pricing behaviors. An entire category may generate a 24% margin, while some customers buy at a 35% margin and another group at only 8%.
Similarly, two sales representatives may generate identical revenue, but one achieves it while keeping discounts under control, while the other regularly sells at the minimum acceptable price. This is why sales performance analysis in Power BI should be expanded to include the perspective of actual realized prices.
Particularly important is the detection of price leakage – situations in which a company loses part of its potential revenue through successive discounts, concessions, and special terms. A single price reduction may appear insignificant. But when similar decisions occur across hundreds or thousands of transactions, they become a systemic profitability problem.
Price Waterfall Shows What Happens Between List Price and Actual Revenue
One of the most useful pricing analyses is the price waterfall. The starting point is the list or reference price. The analysis then deducts each element that affects the actual price, such as a standard discount, sales discount, promotion, retrospective rebate, additional concession, free delivery, or other customer benefits.
Only at the end does the company see the actual transaction price—and, once costs are included, the true margin.
In Power BI, this data can be analyzed by customer, product, order, region, or sales representative. Sales management therefore sees not only the average discount level but also the structure of deviations from the base price.
A natural extension of this approach is customer and product profitability analysis, because price alone does not tell the whole story when individual customers generate very different service costs.
A pricing report can show, among other things:
- average realized price compared with list price,
- value and percentage of discounts granted,
- number of transactions below the agreed margin threshold,
- price differences for similar customers and order volumes,
- margin before and after additional commercial terms,
- share of sales requiring approval for a pricing exception.
Is the Decline in Performance Caused by Price, Volume, or Mix?
Knowing that margin declined by PLN 2 million year over year does not explain why it happened. Part of the change may result from lower prices, another part from volume, and the remainder from the sales mix.
A company may sell more but concentrate its growth on lower-margin products. It may also maintain the same overall volume while increasing the share of customers receiving the highest discounts.
A price-volume-mix analysis helps separate these effects. In Power BI, the company can show how much of the change in performance results from price, how much from the number of units sold, and how much from shifts between products, customers, or sales channels.
This information is far more useful to management than simply being told that margin has declined. It also helps distinguish between a sales problem and a pricing problem.
For trading and distribution companies, it is also valuable to compare realized selling prices with purchase costs. The data required for this type of analysis can be connected with the approach described in our article on Power BI in purchasing and procurement.
Example: Sales Are Growing, but the Company Is Making Less Money
Consider a B2B distributor whose sales in one product category increased by 12% year over year. A standard sales report therefore shows a strong result.
Power BI, however, reveals that the average discount increased from 7% to 10% at the same time, while the share of transactions closed below the minimum acceptable margin almost doubled. Further analysis shows that the issue is concentrated among several major customers and in offers prepared near the end of the month, when the sales team is under pressure to meet its target.
This insight can change the way pricing is managed. The company may introduce thresholds requiring additional approval, different discount limits by product category, or an additional KPI that takes into account not only sales value but also realized margin.
The objective is not to automatically reduce every discount. The goal is to identify which discounts help win valuable business and which simply finance revenue growth at the expense of profit.
Power BI Can Turn Pricing Strategy Into an Ongoing Management Process
A well-designed pricing report should not be used only to analyze the past. Its value increases when it becomes part of the regular work of sales, controlling, and executive teams.
The organization can monitor changes in realized prices, analyze the impact of promotions, control deviations from discount policies, and measure the effect of price increases. Comparing results across customer and product segments is particularly important because a single pricing strategy rarely works equally well across the entire portfolio.
Power BI creates a shared view of the data, allowing discussions about pricing to move beyond individual transactions and sales representatives’ opinions. The company begins to see patterns, the scale of pricing deviations, and their impact on financial performance.
In an environment of cost pressure and growing competition, even a relatively small improvement in pricing discipline may have a greater impact on profitability than another increase in sales volume.