Rethinking PPA Strategy: Lessons from Industry Leaders
Price Pack Architecture (PPA) is a critical tool for aligning pricing, promotions, and mix into a cohesive strategy. This makes it one of the most effective levers companies can use to navigate ongoing market challenges, such as inflation, evolving consumer behaviors, and increasing competition.
Industry leaders Wido Dijkstra (Business Manager a.i. at FrieslandCampina), Haja Deen (Founder at AI Navi, ex-Global Data & Analytics Director at pladis), and Ivan Tretyakov (Director of Innovation at Buynomics) recently joined our roundtable webinar, which explored how PPA, powered by advanced data analytics and AI, is shaping the future of revenue growth management.
The panelists engaged in a focused discussion on how Price Pack Architecture strategies are evolving in revenue growth management (RGM). What was clear is that while PPA remains a strategic lever for companies, there is an increasing demand for data-driven decision-making in today’s PPA strategies.
The key takeaways from this insightful discussion are covered below.
Get the complete picture—watch the full roundtable session for real-world examples and expert insights.
Why is an Evolving PPA Strategy Important?
One of the key reasons PPA is so important is that it serves as the strategic glue, connecting other key RGM levers —such as price, promotions, and trade terms —to ensure they work cohesively rather than in isolation. In most cases, price no longer exists as a standalone element; it is embedded within the context of product formats, pack sizes, and promotion occasions.
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Building on this, the more recent rise in PPA’s importance is due to the increase in available data and technological capabilities that organizations have. The evolution from basic spreadsheets and isolated data marts (a focused subset of a data warehouse, built to serve specific business needs) to advanced data-driven software has given RGM teams unprecedented opportunities to advance their PPA strategy.
Today, AI-driven simulations enable revenue managers to model shopper behavior and test PPA decisions before they hit the market, transforming into a core driver of competitive advantage and sustainable growth. Predictive analytics and AI-driven simulations are now essential for testing PPA scenarios and reducing risk before changes hit the market.
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Real-World Applications: Advanced PPA Strategy in Action
Since Price Pack Architecture acts as the glue across RGM levers, closely interlinked with pricing, mix, and promotions, the most effective strategies avoid looking at pack changes in isolation. Instead, they use PPA to respond holistically to commercial pressures, from inflation to shifting consumer behavior.
In this section, we’ll explore how leading brands have leveraged PPA, in combination with pricing and other levers, to manage rising COGS, maintain affordability, and protect market share.
During the high-inflation period, many brands found that they could no longer rely on pricing changes to optimize their RGM strategies, as prices began to cross key psychological price thresholds.
This led some manufacturers to change their strategy by making portfolio adjustments, such as introducing more affordable pack formats. For example, taking a dessert traditionally sold in four-cup packs and introducing a single-cup format for a lower price point. This allows customers to stay below a certain psychological threshold, such as one euro, while ensuring revenue for the manufacturer. This example illustrates how PPA can be leveraged strategically to navigate inflationary pressures and maintain market share.
Want more real-world examples of how PPA can be used to achieve sustainable growth? Download our case study.
Another good example comes from Unilever, which used PPA changes to overcome affordability challenges in low-disposable-income markets. To achieve this, they adopted a specific PPA strategy, downsizing products to individual sachets for essentials such as shampoo and detergent, which were sold in traditional trade shops. These sachets provided affordable access to everyday goods for consumers with less disposable income.
In addition to these portfolio adjustments, some companies have moved further, adopting more advanced, data-driven approaches to optimize PPA and better anticipate commercial outcomes. One example is pladis, a global snacking company, which sought to counter rising COGS and improve decision-making by using advanced scenario modeling to optimize its Price Pack Architecture. Learn how they did this in the video below.
Where Do Companies Currently Stand on PPA Maturity?
Traditionally, PPA decisions relied on heuristics, such as the Occasion, Brand, Pack, Price, and Channel (OBPPC) framework. While this remains important for PPA decisions, using this manufacturer-centric approach alone can fail to capture shopper behavior and account for changes in your product portfolio, taking into consideration competitor moves and category dynamics, which can leave manufacturers missing their revenue goals.
Yet despite the growing importance of getting PPA strategy right, many companies have yet to evolve their approach fully. This is shown in a live poll that ran during the webinar, where 51% of participants revealed that most organizations are still in the “exploring and testing” phase when it comes to making scalable and profitable PPA decisions. Only 13% reported full integration, and a further 1% reported a fully scaled data-driven PPA strategy with proven ROI.
Source: Rethinking PPA: Strategies from Inside the Industry
In a previous poll among revenue growth managers conducted during one of our past webinars, 80% of participants stated that PPA is becoming “more” or “much more” relevant for their organizations. Given the importance of PPA, this means that many organizations risk being left behind by those who advance their RGM maturity faster. This gap between aspiration and implementation highlights a clear opportunity: while many recognize the value of data-driven PPA, few have fully capitalized on it.
How Can Organizations Advance Their PPA Strategy?
As the glue that connects pricing, mix, and portfolio decisions, a well-developed PPA strategy ensures cohesion across all RGM levers. The insights shared in this panel demonstrate how enhancing PPA strategies with AI-powered tools that empower data-driven decision making can help organizations remain competitive, protect their margins, and better serve their shoppers.
For RGM leaders still navigating early stages of PPA maturity, the message is clear: the tools and strategies are available, and those who adopt them into their existing strategy first will be better positioned to lead. To empower manufacturers to address PPA changes holistically alongside other RGM levers, Buynomics introduced the Virtual Shoppers AI technology.
Buynomics' Virtual Shoppers AI is a machine learning algorithm that combines the fundamentals of behavioral economics with manufacturers’ customer data, resulting in the creation of millions of AI agents that can predict shoppers' behavior with 95% accuracy.*
The Virtual Shoppers AI reflects actual shopper behavior and can predict how shoppers switch between products after a PPA change, such as the introduction, removal, or change of a pack size. Will they choose your product, a competitor, or decide not to buy at all?
Answering this question enables manufacturers to evaluate the precise impact of their actions on the entire portfolio and category level (see the short demo video below).
Request a demo to see how Buynomics helps RGM teams design, test, and optimize Price Pack Architecture with precision, driving growth, protecting margins, and staying ahead of the market.
* depending on the data quality
