Marketing & Sales
Competitive pricing with a dynamic model in telecom
In the telecom sector, staying competitive means constantly benchmarking product pricing across operators and markets. Agilytic partnered with a Belgian telecom company to replace a manual, error-prone pricing process with a dynamic model, enabling faster and more reliable competitive analysis.
To protect confidentiality, we may alter specific details while preserving the accuracy of our core contribution.
Context and objectives
A Belgian company operating in the telecom sector needed to regularly compare the prices of its products and services against competitors across multiple countries. The existing process relied on Excel spreadsheets maintained manually, which was time-consuming and prone to human error.
The company wanted to:
Optimize the selection of telecom products and the combination of products under predefined constraints
Automate price comparisons across operators and geographies
Provide a user-friendly interface so business developers selling telecom and media services could interact with the results directly
Agilytic was brought in to develop an algorithm and interface to automate the entire process.
Approach
Data preparation and product combination logic
The first step involved cleaning the raw data stored in Excel. From there, Agilytic created combinations of products and services to ensure that even when no standalone pack matched the selected criteria, a combination of packs or SIM cards could meet the constraint.
Profile-based pricing optimization
To make the results actionable for business developers, Agilytic associated packs with relevant client profiles provided by the company. The goal was to identify the cheapest internet, TV, and phone packs matching each profile's characteristics, turning raw data into a practical dynamic model.
Visualization, automation, and handover
Agilytic built Power BI visuals and an executable Python file that runs all scripts to compare prices. The dynamic model in Power BI allows users to filter by period, country, or pack type.
To ensure long-term autonomy, Agilytic also delivered:
Full documentation of the solution
Training sessions on the Power BI software for the client's team
The main deliverables were Power BI visuals, Python scripts, and an executable file to run the scripts and update the files that Power BI reads.
Results
The dynamic model saved significant time and removed manual errors from the process. It made it easy to compare telecom packages against a series of predefined characteristics. Specifically, the solution made it possible to:
Run the necessary scripts in 5 minutes
Load visuals with real-time data in 10 minutes
Change target profiles directly in Power BI
Generate clear visuals for inclusion in annual reports
With quick oversight of offers and packages, the client now makes better pricing decisions, helping them stay competitive in the fast-moving telecom sector.
To safeguard confidentiality, we may modify certain details within our case studies.