The economic disruptions from the COVID-19 pandemic and high inflation changed the way consumer-packaged-goods (CPG) companies achieved sales growth. Prior to 2020, pricing and volume propelled sales growth, with pricing as the leading factor. However, a sustained period of high inflation spurred a much greater shift toward price-driven growth, with volume declining or staying relatively flat for the vast majority of consumer goods categories.
Now, as inflation may be reverting to long-term norms, the pendulum is starting to swing. Adjusting prices is less of a guaranteed path to growth. In fact, retailers are beginning to increase promotions to help cover volume losses. Yet volume growth remains elusive, especially with consumers continuing to trade down and swap brands for private labels. This changing landscape is challenging for businesses looking to sustain growth by finding the right balance between price and volume.
Companies looking to navigate these uncertainties can reboot their approach to revenue growth management (RGM). Of the four levers of RGM—pricing, promotions, assortment, and trade investment—companies have largely focused on the first, taking a relatively blunt approach of increasing headline prices during inflation to drive net-price realization. But now, a more nuanced approach using all four levers could serve companies better, and increased sophistication is required.
In this article, we first describe the price elasticity that CPG companies have seen in recent years. Then we make five recommendations for business leaders: setting grounded long-term aspirations, deeply understanding consumer behavior, deciding which RGM levers to pull, engaging retailers in new ways, and improving tech capabilities. By following these steps, businesses can position themselves for success in a rapidly evolving market and for better management of changing pricing dynamics.
Price elasticity during inflationary times
In the years leading up to 2020, most consumer goods companies reliably delivered mid-single-digit net-sales growth. According to our analysis of the top 32 publicly listed CPG companies, this growth was driven slightly more by price than by volume. In 2020, growth stagnated as a result of the pandemic. In the 2021 boom, both price and volume rose about 3 percent. In 2022, the pendulum swung heavily. Hyperinflation pushed prices up by more than 10 percent, volume decreased, and yet overall net sales remained high because of the steep price increases. In 2023, inflation reduced somewhat, decreasing net-sales growth, but volume didn’t return. So far, 2024 is delivering much lower price growth and continued volume declines (Exhibit 1).
Not surprisingly, this swing toward price dominance in sales growth has caught the attention of analysts and investors who are sensitive to volume losses, given category volume declines. Company executives tell us that they have sought to reassure investors of their intention to plot a path to a more balanced and sustainable mix of price and volume-driven growth.
Rebooting revenue growth management
With shaky total shareholder returns in recent years in the CPG sector, investors are rightly uneasy about whether companies can spur higher growth rates by balancing price and volume. Whether they raise concerns about price elasticity increasing again or retailer pushback on price increases as commodity costs turn more favorable, the broad consensus is that managing pricing in the coming months and years won’t be easy. As inflation recedes, so does the potential of the pricing lever.
More sophisticated RGM capabilities beyond pricing will be critical to continue to drive net-price realization and growth. Companies can improve their odds of delivering more balanced net-sales growth by reactivating the full range of RGM levers to adjust prices, expand higher-margin items in their portfolios, and maintain or increase overall volume. Here are five areas of focus they can consider.
1. Set grounded aspirations for multiple cycles
Globally, central banks are indicating a potential soft landing for the economy, suggesting that inflation could return to prepandemic levels within a couple of years. The US Federal Reserve forecasts annual inflation of 2.6 percent in 2024, falling to 2.3 percent in 2025, and stabilizing at 2.0 percent in 2026. The European Central Bank estimates a similar reduction in inflation over the same period: 2.5 percent in 2024, 2.2 percent in 2025, and 1.9 percent in 2026.
While no one knows exactly how things will play out, these projections provide a useful reference point for CPG companies planning price realization strategies over the next three years. If inflation does indeed hover around 2 percent, these companies should expect to return to a 2 percent price-mix realization coupled with a modest volume increase of another 1 to 2 percent, depending on the growth dynamics of the category. Top-performing companies that excel at RGM strategies and implementation will aim to beat this baseline scenario.
Companies should view incremental net-sales growth explicitly as a function of the specific advantages they enjoy in their respective categories. These advantages might include a superior brand that’s less price sensitive, a distribution footprint skewed toward high-growth channels, or a presence in high-growth subsegments. Additionally, explicit actions—such as innovation with new product launches, incremental distribution with more SKUs in existing channels or existing SKUs in new channels, and greater marketing effectiveness—can help companies outperform the baseline.
2. Get to know your consumers better
Even with positive macroeconomic indicators, companies should pay close attention to trends in consumer and household sentiment and behaviors. According to consumer price index data from the Bureau of Labor Statistics, US inflation was 2.7 percent in November 2024, compared with its peak of more than 9.0 percent in June 2022. The cost to feed a family of four is now 51.6 percent higher than prepandemic levels, heavily outpacing disposable income growth, which has risen by 30.3 percent in that same period.1 And although, in September, the Federal Reserve announced its first interest rate cut in more than four years, interest rates are still well above prepandemic levels, and personal monthly interest payments are up 50.1 percent.2 A recent McKinsey ConsumerWise survey shows that although US consumers have grown a bit more optimistic, they remain cautious about spending. They’re cutting back, changing to discount retailers, shifting to private labels, or simply delaying purchases, with 74 percent of US consumers changing their shopping behavior to trade down (Exhibit 2).
To ensure that RGM strategies are effective, companies should develop a deep understanding of how core consumers might respond to any price-related move. Aggregate views should be unpacked by category, consumer segment, and brand. For example, a given consumer segment might abandon its favorite brand and switch to private-label spices at primary grocers, or it may choose not to abandon the preferred brand and instead go to club retailers and upsize for a lower price per ounce or kilogram. Consumer behavior is differentiated; people may choose to save in some categories but increase spending in others. The more a company is able to understand what its consumers think and how they behave, the more precisely it will be able to calibrate any pricing and RGM changes.
3. Develop a chessboard of moves with RGM levers
Many companies may set ambitious net-sales-growth targets to exceed the baseline case, but fewer have a clear plan for success. That said, there are enough arrows in the RGM quiver for companies with the right know-how to improve their odds. Using the right RGM tactics—in the right proportion, for the right brand, and on the right channel—helps set companies apart (table). There’s a premium to capture by getting this right. Companies that use RGM to achieve net-price increases with the most muted price elasticity effect or to outperform in volume growth will likely have a distinct competitive advantage.
At a high level, companies should start by understanding the relative net elasticity effect of a given “net price” action. For example, a 10 percent increase in manufacturer’s suggested retail price (MSRP) has a more tangible impact on a consumer than an equivalent increase derived from optimizing promotions, focusing on higher-end products to encourage higher margins, or resetting trade terms with retailers. All the latter actions deliver net-price gains—but with less impact on consumers.
Different revenue-growth-management tactics have varied impact on elasticity.
| Higher perceived impact on consumers | Lower perceived impact on consumers | |||||
| Tactic | Manufacturer’s suggested retail price (MSRP) | Pack size/weight | Promotions | Product mix | Channel mix | Trade terms/gross to net |
| Example | 10 percent increase in nonpromoted price to consumer | Hold opening price point while flattening discount slope for large pack sizes and for weight in any given pack | Eliminate lowest ROI promotions and test reducing consumer promotions funding | Drive distribution and sales of more premium-priced products | Drive sales in channels that deliver higher net prices | Reduce loss from spoilage allowances |
RGM tactics are strategically tailored to how consumers perceive their value and impact. For example, direct pricing changes, such as increasing the MSRP, affect what people pay at checkout. These price adjustments are highly noticeable and can influence purchasing decisions immediately.
Other tactics such as altering pack sizes, reducing the frequency of promotions, or shifting the product mix toward premium items might also be noticed by consumers, but they generally have a slightly lower perceived impact. These changes influence consumer behavior more subtly, often by affecting perceived value rather than outright cost.
Behind-the-scenes strategies such as optimizing sales channels or reducing nonproductive trade investment have the least impact on consumer perception. These actions are designed to maintain or enhance profitability without making obvious changes that would draw consumers’ attention, thereby preserving a sense of value and stability.
Whether these various tactics achieve desired outcomes depends on factors such as underlying category dynamics, strength of a given brand, and a company’s execution capabilities (Exhibit 3). No plan fits all: companies that straddle multiple categories and brands will need to tailor their own solutions, involving precise price points, promotional investment, and distribution channels.
4. Double down on tech capabilities
Effective data strategies and AI can help companies navigate the complexities of consumer behavior and market dynamics, and even develop recommendations that encourage both price realization and volume growth. However, many CPG companies struggle with implementing the right technology. Consider what it might take to develop the right MSRP recommendations to help a hypothetical brand achieve above-inflation price realization while increasing volume. This brand might feature 30 different SKUs across pack sizes, product formats, and categories. Each SKU could have unique competitive strengths, regional selling dynamics, cross-channel shopping behaviors, elasticities, switching tendencies due to price changes, and promotion responsiveness at different price points. Getting to the optimal granular solution would entail considering hundreds, if not thousands, of scenarios. This cannot be done successfully without high-accuracy predictive and automated technology, supported by robust shopper analytics.
To illustrate the power of advanced tech solutions, consider a real-life example. A food company set prices based on its own brand elasticities, using shopper analytics to estimate the outcome of pricing decisions. However, it found that actual buying behavior differed significantly from its pricing simulations, making the approach ineffective. As a result, the company decided to increase the sophistication of its methodology in two ways.
First, it added new shopper analytics that assessed switching behavior between SKUs. The company discovered that a significant part of the volume losses for a SKU was flowing back into its own portfolio through other SKUs and brands. The switching analytics enabled it to understand net portfolio elasticity from portfolio price changes, rather than just the elasticity of individual SKUs (Exhibit 4). This also changed the company’s view of its competition. In many cases, the SKUs with the highest switching rates were not from expected competitors.
Second, the company developed a high-accuracy, AI-enabled predictive and prescriptive simulator that suggested portfolio pricing changes based on optimization under constraints—for example, to maximize profit while maintaining market share, the company’s RGM analyst can ask the simulator to propose pricing changes for all SKUs in the portfolio. The company can now make thousands of tech-powered simulations in seconds, significantly improving both the impact of the price changes and the accuracy of the prediction while reducing the time spent on pricing analyses.
Advanced tech solutions are also being deployed to assess the longer-term impact of promotions on household penetration, rather than narrowly deriving short-term promotional ROI from incremental sales during a promotions period. By aggregating myriad data sources—such as loyalty, syndicated point-of-sale, and social sentiment—machine learning and AI can discern patterns that help companies develop recommendations that get closer to efficient promotional spend. For example, through strategic partnerships that gave it access to anonymized retailer loyalty data, a leading CPG company increased its household penetration by redeploying funds from subsidies for brand loyalists to product trials for nonusers.
Generative AI (gen AI) also adds an exciting new layer of possibility, particularly in aiding the adoption of RGM technologies. Gen AI can deliver tangible short-term benefits for RGM, such as streamlining how RGM analytics are presented to the many stakeholders responsible for sanctioning and executing RGM decisions or speedily crafting more engaging, resonant sell-in stories for retailers. Companies are already beginning to explore these opportunities, enabling more effective RGM processes.
Getting the right technology in place is just part of the answer. Most CPGs struggle to scale from an initial pilot to an enterprise capability. Implementing sustainable RGM digital and AI capabilities requires a comprehensive approach that goes beyond technology, focusing also on key enablers such as data integration, cross-functional collaboration, and change management practices.
5. Find new ways to engage retailers
The dynamic between consumer goods companies and their retail counterparts creates a healthy tension that leads to efficient outcomes for consumers. However, this tension can also prove challenging. For example, retailers are significantly increasing promotions on key value items. CPGs often view these promotions as destructive to category value. Two ways for CPGs to proactively move away from these clashes are retail media networks (RMNs) and data acquisition.
First, most major retailers now operate substantial RMN businesses, advertising products and brands on their e-commerce platforms. CPGs are spending millions on these networks. However, sometimes there’s little visibility between the sales team negotiating pricing and trade terms and the marketing team negotiating media spend on RMNs. To get a holistic view on their commercial spend, leading companies are beginning to integrate these teams. Now is an opportune time to engage retailers on ways to connect pricing more optimally to RMN activation. For instance, combining a CPG company’s RMN budget with its promotions budget to run integrated omnichannel, multimodal campaigns could harmonize online ads with in-store promotions and provide greater visibility into the incremental lifetime value of a consumer. This is a promising avenue for consumer goods players to pursue.
Second, many retailers are now de facto data vendors. Take, for example, Walmart’s Luminate venture or British grocer Tesco’s dunnhumby, both data analytics platforms that preferred vendors can use to understand how shoppers shop. Vendors can see their performance against category performance and learn whether they’re gaining or losing share compared with their competitors. CPG companies should be getting ahead in finding ways to take advantage of access to this kind of granular data on SKU sales across all sales channels to build more robust models and have more strategic discussions with retail partners.
Companies that do a better of job of engaging retailers in a way that tailors to retailers’ positions, leverages their specific data, and makes clear the value that proposals bring to retailers and shoppers may well propel greater price and volume growth.
The current landscape is likely to be among the more challenging in recent memory for consumer goods companies looking to increase net sales. The era of “easy pricing”—raising prices in a blunt way on the back of inflation spikes—is likely over, and unit consumption growth is a pressing concern. RGM practitioners can help their companies navigate and outperform with a clear-eyed and tailored approach that sets realistic aspirations in the context of the macroeconomic conditions. They can beat the odds with smarter use of AI and gen AI to better align stakeholders and engage retailers. Companies that excel could see as much as a 1.2 to 1.5 times net-price realization above baseline inflation while boosting consumption at category-level rates. That’s a worthy goal—and more than enough of a reason to get this right.
