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How a Snack Producer Reached a Net Sales Uplift by Finding the Optimal Price Increase

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£2Million

Revenue potential was identifiedby implementing a stable everydayprice with >90% distribution.

x3.5ROI*

Delivered through the Buynomicsplatform, which accurately forecaststhe impact of price and distributionchanges on the market.

* The 3.5 times ROI is based on only one decision, unlimited decisions can be analyzed and taken with the Buynomis tool.
Future-proofing RGM with AI

Background

Price  Promotion  |    iconscasestudyanon03  Food | >10B | iconscasestudyanon01 Global

 

The global food producer, renowned for its specialization in snacks, has firmly established itself as a leader in the industry.

Its iconic product lines, featuring a diverse range of beloved offerings, have become a household staple for millions worldwide.
This prominence is reflected in its impressive financial performance, with net sales surpassing $10 billion in 2023.

The manufacturer planned to increase net sales in 2024 and wanted to make sure they understood shoppers' reactions to the chosen growth strategy in advance.

This approach involved leveraging data-driven insights to optimize RGM levers to consumer preferences, ultimately ensuring sustainable revenue uplift and strengthening brand positioning.

Challenges

The manufacturer aimed to grow their net sales by strategically optimizing two key Revenue Growth Management (RGM) levers: Price and Promotion. Efforts to refine the Price Pack Architecture (PPA) were constrained by manufacturing limitations.


Manufacturing constraints

Limitations in refining Price Pack Architecture (PPA)

 


Market dynamics

Adapting to evolving market conditions with price increase and promotion strategy.

 

Tested Strategies

 

Strategies Tested

  • A price increase from £2.70 to £3.00 for a specific snack product in their portfolio, without offering promotions and having a close-to-full distribution.
  • The manufacturer had an everyday low-price strategy before and wanted to test a high-low promotion structure that involved frequent medium-depth promotions but with reduced distribution.

 

Results

Price Increase: The optimal scenario identified: An everyday–low-price of £3.00 with close-to-full distribution will ensure the required net sales uplift.

High-Low Promotion Structure: The High-Low promotion strategy was declined because shoppers have an inelastic response to the price decrease, which meant that the promotion was not enough to compensate for distribution lost.

Results

With the Buynomics software, the team was able to model a price increase and different promotion strategies holistically, benchmark their performances, and make decisions fully understanding the impact the changes will have on their net sales.

£ 2 Million

Revenue potential was identified
by implementing a stable everyday
price with >90% distribution.

 

x3.5 ROI*

Delivered through the Buynomics platform, which accurately forecasts the impact of price and distribution changes on the market.

 

*The 3.5 times ROI is based on only one decision, unlimited decisions can be analyzed and taken with the Buynomis tool.

Make better RGM decisions, faster!

Run agent-based simulations with Buynomics’ Virtual Shoppers AI to optimize all revenue levers, capturing cross-effects, cannibalization, and competition.

2-4%

Profit impact*

95%

Predictive Accuracy*

80%

Faster Decision-making

*Depending on data quality and completeness