How precision revenue growth management transforms CPG promotions

Consumer-packaged-goods companies are learning that the insights derived from advanced analytics capabilities enhance promotion performance—and the bottom line.

Promotions have always been an important sales driver for consumer-packaged-goods (CPG) companies. Analysis has shown that 28 to 50 percent of retail sales volume across CPG categories in Europe is based on promotions. 1 Some CPG companies invest up to 20 percent of their gross revenues on promotions, making it one of the largest items on the profit and loss (P&L). 2

As one of the four levers of revenue growth management (RGM)—along with pricing, assortment, and trade investment—promotions may be even more important now, with consumers switching brands and products at unprecedented rates. Our research shows that across Europe, Brazil, China, and the United States approximately 30 to 40 percent of shoppers have tried new brands during the COVID-19 crisis. 3 Promotions have the potential to capture a large portion of their business.

Nonetheless, despite these statistics, CPG companies still struggle to capture the full value of promotions as growth drivers. That’s because visibility into the net short-term and long-term impact of their promotions is surprisingly poor, given the size of their investment. CPGs often, for example, don’t have a granular understanding of the return on investment in promotions beyond the short term, the influence of promotions on shoppers’ behaviors, or the impact of promotions on retailers’ sales beyond the CPG companies’ own brands.

This issue played out at one European CPG company, where sales and marketing leaders could not get sufficiently detailed insights into the longer-term implications of promotions. They did not know, for example, whether consumers continued to buy their products once a promotion was over, nor did they know what the impact of promotions was on shoppers’ overall basket size during the promotion. They also could not quantify the category impact that its promotions had on retailers, which meant they had little leverage when negotiating with them.

This company is not alone. The vast majority of CPG manufacturers have limited promotions capabilities. Indeed, nearly half of all large European CPG manufacturers report that they have no trade-promotions optimization tool. Almost none analyze the longer-term effects of promotions on shopper recruitment and household penetration, or use the insights to boost longer-term market-share growth. In a recent survey, in fact, 58 percent of CPG companies identified the need for data, analytics, and a better understanding of changing consumer trends as major challenges to delivering on their growth aspirations.

Keys to new world of promotion insights

The explosion of available data, often built on partnerships with new data providers or retailers, along with advances in analytics, have allowed businesses to extract more insights and make better decisions.

Leading CPGs are building on this trend as their promotional capabilities mature. Those companies that have seen the greatest impact from promotions (and from RGM in general) have been investing in analytics and data to drive greater precision as part of a broader RGM strategy. In particular, they’ve invested in accessing and leveraging household-panel and retailer loyalty-card data in addition to traditional point-of-sale and internal financial data. These investments have enabled them to create increasingly sophisticated promotional campaigns that drive both short- and long-term impact (Exhibit 1).

There are four maturity levels for maximizing promotion value.
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In our experience, however, most companies stall at level-two promotions maturity, with no clear path to move to level three or four.

More advanced CPGs have extensively analyzed their data (both traditional and new sources) to develop predictive algorithms, which they then constantly test and adjust. This has enabled them to progress to promotion-impact-simulation tools (level three), which aid key account managers’ decision making by providing a strong fact base about the potential impact of changes. In the most advanced capability (level four), CPGs can assess the longer-term impact of promotions on household penetration and on the retailer (at both the category and full-basket level), and enable microtargeting by pinpointing the promotional preferences of shopper segments.

CPGs that invest in these capabilities are finding they can drive new growth in stable to declining markets. Here is how the European CPG mentioned above did it.

How one company built up its precision promotions capabilities

In order to overhaul how it managed its promotions and to reach its goal of category and regional leadership, the European CPG company knew it needed better data. So it gathered existing standard syndicated sales and internal financial data and complemented them with newly acquired anonymized retailer loyalty-card data, as well as geographic and demographic data. 4 This enabled it to segment and assess consumption patterns at an anonymized shopper level.

To process this extensive dataset, which comprised several million anonymized shoppers and hundreds of millions of transactions, the company established a multidisciplinary team of RGM analysts and data scientists, and deployed a sophisticated algorithm to detect patterns of consumption and promotional performance at the level of single transactions and shoppers.

The insights into the true value of promotions challenged the company’s established beliefs with quantitative evidence. It found, for example, that in the short term, the company’s promotions were more successful than its competitors’ in terms of growing the overall value of a shopper’s basket (Exhibit 2). By explaining this to retailers, the company was able to increase the visibility and share of its promotions.

Advanced analytics quantify the short-term impact of promotions for category development.
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The analyses also revealed that there were significant differences in shopping behaviors and preferences at different points of sale. For example, through analyzing the granular shopper-level data, it found that its promotions sales were under-indexing with price-sensitive consumers, with whom the company was overall under-penetrated and who preferred to buy smaller entry product formats, or larger value-for-money packs. This drove the company to increase the number of promotions it ran in smaller product formats to meet those preferences and increase penetration.

Over the mid to long term, the analyses showed that certain promotions that were not price-based, such as offering collectibles, were more effective in recruiting consumers to the brand than price promotions, and drove long-term value despite the initial negative ROI.

Building on these insights, the company introduced a new system to evaluate the impact of promotions. When it needed to boost volumes quickly, for example to defend market share, it introduced tactical promotions that delivered short-term sales uplift. But when shopper penetration and recruitment were the strategic goals, the business was able to shift to promotions that delivered over a longer term.

With this baseline of tested insights, the company developed a predictive simulator powered by a proprietary algorithm. Starting from past observations, this simulator automatically builds patterns of future promo efficiency and effectiveness, and allows the sales team to quickly and easily deploy promotions and assess their expected future impact on sales uplift and financial returns. This has led to three major changes:

  • key-account managers can now zero-base their promotional plans rather than incrementally adapt last year’s promo calendar based on limited insights
  • the appeal of promo plans has greatly increased for retailers, as the simulations of retailer impact create win-win promo plans, and the insights are shared with the retailers
  • key account managers are now empowered to work directly with the RGM insights rather than get recommendations from the RGM team, which increased the use of, and belief in, these insights

With this capability, the company has been able to increase sales by an additional 1 to 2 percent and EBITDA by 4 to 5 percent, resulting in an increase of one to two percentage points in EBITDA margin and the capture of significant value during the first year of implementation. Collectively, the improved performance of promotions has contributed significantly to advancing the company’s market-leadership ambitions.


Many CPG companies are stymied because they do not know how (or think it will be too hard) to make the leap toward much greater transparency on the true impact of promotions. The reality is that getting quick results is feasible. To start, CPG companies should pilot the approach in markets or categories where anonymized shopper-level data is available, promotion volumes are high, and some existing ROI capabilities are in place. The value at stake in the next normal—and the growth challenge facing CPG companies—are too big to wait any longer.

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