Circana: Data-first pricing helps CPG brands diagnose demand and protect profits

CHICAGO — As inflation, changing consumer behaviors, and fierce retail competition reshape the consumer packaged goods industry, pricing decisions have become one of the most impactful strategic tools for brands. According to a new analysis from Circana, authored by Christina Chambers, a data-driven pricing approach can help brands assess current performance, understand price sensitivity, and forecast future outcomes before making pricing adjustments.

The report explains how small and mid-size CPG companies can lower pricing risk by basing decisions on measurable demand signals instead of relying on topline sales trends or promotional calendars.

Start with a Business Review

Circana’s analysis indicates that pricing strategy should start with a clear understanding of how current pricing and promotion tactics perform. While topline sales often dominate internal discussions, they rarely reveal whether promotions create additional demand or just subsidize purchases that would have happened at regular price.

A structured business review can help brands diagnose several key factors, including:

• Promo penetration: the share of sales occurring during promotions
• Incremental contribution: whether promotions drive new demand or cannibalize base sales
• Subsidization rate: the percentage of promoted sales likely to have occurred at base price
• Event ROI and efficiency: which promotional mechanics generate the strongest returns
• Post-promo behavior: whether demand rebounds or dips after promotional activity

Circana points out that this kind of analysis can reveal hidden inefficiencies. In one example from the report, a frozen entrée brand found that about 60% of its volume was sold on promotion, well above the category average. Further analysis revealed that roughly 40% of promoted sales were subsidized rather than incremental, leading the brand to cut back on promotion frequency and reduce discount depth while keeping baseline demand stable.

Measuring Price Sensitivity

Once brands understand current pricing performance, the next step is to determine how consumers will respond to price changes.

Price sensitivity, often called price elasticity, measures how demand reacts when prices go up or down. Understanding elasticity helps brands see where increasing prices is possible, where demand is weak, and where there is room to adjust prices.

For growing brands with fewer SKUs and narrower margins, this analysis is especially crucial. A poorly timed price hike can quickly damage distribution gains or retailer support. By measuring elasticity across SKUs, retailers, and channels, companies can identify where adjustments can be made with minimal risk to volume.

Simulating the Impact of Pricing Changes

With elasticity models in place, companies can shift from analysis to scenario planning. Circana emphasizes the importance of price simulation tools that estimate how potential changes, such as base price increases or reductions in promotional discounts, might impact volume, revenue, and profit.

Simulation models can help brands answer questions such as:

• What happens to revenue and margin if base prices increase by 5% or 10%?
• How would reducing promotional discounts affect unit sales and trade spend?
• Which retailers or regions are best positioned to absorb a price increase?
• Which SKUs are most sensitive to price adjustments?

For example, the analysis shows how a challenger soda brand, considering a price increase on multipacks, used simulation modeling to identify regions where demand was less sensitive. By selectively raising prices in those markets, the company maintained sales velocity while boosting revenue.

In another case, a condiment brand decreased promotional depth from 30% to 20% and found that the change had little effect on volume while greatly boosting promotional return on investment.

Building a Repeatable Pricing Discipline

Chambers argues that pricing should be treated as an ongoing discipline rather than a one-time adjustment. Circana outlines a four-step workflow for brands:

1. Business review: Evaluate promotion performance, incrementality and post-event demand behavior.
2. Elasticity measurement: Estimate demand sensitivity across SKUs, retailers and channels.
3. Scenario simulation: Model potential pricing strategies and their impact on sales and margins.
4. Decision and alignment: Develop a cross-functional pricing plan supported by data and retailer rationale.

In an environment where costs, competition, and consumer expectations are constantly changing, Circana’s analysis finds that pricing must go beyond reactive adjustments. A data-driven approach helps brands protect margins, sustain demand, strengthen retailer relationships, and support long-term growth.