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cloud.google.com·6h ago
AI Research
arXiv CS.AI·Aug 20·5 min read
Budget-First Tariff Recommendation (BFTR): A Complete Algorithmic Framework for Telecom Plan Recommendation without Overcharging
TL;DR
Budget-First Tariff Recommendation (BFTR) is a novel algorithmic framework for telecom plan recommendations that ensures zero overcharging by aligning final prices with catalog reference prices. It integrates eight strategies, demonstrating optimal customer utility and budget usage through empirical testing.
✦ Why It Matters
Telecom companies can implement BFTR to enhance customer satisfaction and eliminate overcharging in their pricing models.
Key Takeaways
- Implement BFTR to align prices with catalog references.
- Utilize Recursive Hybrid for optimal customer utility.
- Adopt Piecewise for maximum data volume offerings.
- Adjust weighting parameters to refine utility rankings.
How It Works
BFTR employs eight strategies to recommend telecom plans based on user budgets. The Recursive Hybrid approach uses conditional interpolation to optimize plan selection, while the Knapsack-First Hybrid prioritizes budget allocation.
Each strategy is designed to ensure that the final price does not exceed the catalog reference price, thus preventing overcharging.