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How a Skin Care Company  Identified a 15% Potential Profit Uplift by Optimizing Their Prices

+15%

Potential profit uplift

>85%

Accuracy predicting sales impact

Background

Promotion Price      iconscasestudyanon03  Beauty & Personal Care |  iconscasestudyanon01 Global

 

The client, a skincare product manufacturer, distributes their products through both online and offline pharmacies and retailers. They sought to shift towards a more data- driven approach for pricing strategy.

The objective was to utilize data to better understand price elasticities and the effects of pricing decisions on their own and their competitors' product portfolios.

To achieve this, the client partnered with Buynomics to estimate and validate the impact of price increases on sales volumes.

Challenges

The manufacturer choose to implement Buynomics’ software due to its holistic approach and Virtual Shopper AI technology, which simulates thousands of scenarios to predict how the shopper will behave in front of the supermarket shelf.


Lack of holistic approach

The absence of a holistic approach hindered their ability to streamline and accelerate data-driven pricing analyses.

 


Margin pressure

The manufacturer's cost base increased because of rising raw material prices. This surge in material costs has put additional pressure on their overall production expenses.

 

Tested Strategies

By partnering with Buynomics, the team successfully modeled price and availability changes. The insights from Buynomics' software, which highlighted the impact of price changes on the category and the market, were crucial for the manufacturer during negotiations with retailers and pharmacies.

 

Strategies Tested

  • Price changes for own and competitor products
  • Availability changes

 

Results

The optimal price increase scenario identified a potential 15% revenue uplift. 

Results

+15%

Potential profit uplift
in offline sales channels.

 

>85%

Accuracy predicting  sales impact allowed the manufacturer to minimize the risk of negative effects on sales volumes.

 

 

Understanding a Price Elasticities Range

Buynomics identified product price elasticities, mainly ranging between -1.3 to -0.1 at offline channels and -3 to -0.5 at online channels.

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