Skip to main content

New Insights: The Future of RGM Report 2026 👉 Download now

How a Mobile Network Operator Leveraged Pricing Optimization to Identify Revenue Uplift Potential

4-15%

Revenue uplift potential identified.

01. Background

iconscasestudyanon04  Price    |    iconscasestudyanon03  Telecommunication   |    iconscasestudyanon01 Global

The global telecommunications provider offers mobile, broadband, and digital services across
Europe, Africa, and Asia. Its vast network and customer-first innovations have made it a household name, generating over €40 billion in revenue in 2023.

Amid fast-paced market dynamics, the company faced increasing pressure to keep its commercial offerings competitive while adapting to evolving customer expectations.

02. Challenges

The telecom provider was under pressure to protect market share amid rising competition and necessary price increases. At the same time, slow, inflexible pricing research methods limited its ability to respond quickly and effectively in a fast-paced market.


Increasing competition

Amid increasing competition from low-cost Mobile Virtual Network Operators (MVNOs), the telecom provider faced the dual challenge of maintaining market share while implementing necessary price increases to offset rising operational costs.

 


Limited agility in revenue impact

The company needed a faster, more comprehensive way to understand the impact of pricing changes. Traditional conjoint studies were time-consuming, limited in scope, and lacked the agility required for timely decision-making in a fast-moving market.

 

03. Approach

Using Buynomics, the Insights & Analytics team set the following requirements to look for the best solution:

 

Changes tested:

Pricing and portfolio changes for own and competition offerings.

 

KPIs to optimize

Revenue and units.

 

Impact assessed

Portfolio and category levels.

 

The Buynomics software, powered by Virtual Shoppers AI technology, gave the team the flexibility to instantly assess the impact of these requirements at both portfolio and category levels, enabling confident, data-driven decisions based on a clear understanding of customer behavior.

04. Solution

The team rapidly tested hundreds of pricing and portfolio scenarios, narrowing them down to the most effective options and then choosing the one that had the biggest positive impact.

 

The following four key scenarios were selected as benchmarks to support final decision-making:

 

Portfolio Structure

1. A flat €1 increase was applied to all plans from one brand, while competitor pricing remained unchanged.

 

2. A flat €1 increase was applied to all plans from one brand, with competitor pricing matched accordingly.

 

3. A flat €5 increase was applied to all plans from one brand, with competitor pricing remaining unchanged.

 

4. A flat €5 increase was applied to all plans from one brand, with competitor pricing matched accordingly.

 

 

Results

Testing hundreds of different pricing and portfolio scenarios, we found that:

 

€1 and €5 price increases, while competitor prices remained unchanged, led to up to 38% sales volume declines. Revenue dropped by up to 43% as customers shifted to smaller packages or alternative offers.

 

€1 and €5 price increases, with competitor pricing matched, led to sales volume declines of up to 12%. Despite this, revenue increased by up to 15% as customers absorbed the higher prices across the market.

 

 

05. Impact

With Buynomics, the team modeled price increases, benchmarked performance against competitor moves, and made rapid, data-driven decisions. The platform provided full transparency into the impact of each decision and answered key “what-if” questions with speed and precision.

4-15%

Revenue uplift potential was identified by modeling own and competitor price increases.

 

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