In a competitive environment where customer retention is crucial, telecom operators are constantly looking for ways to optimize their revenues. Upselling, which involves encouraging customers to choose higher-tier offers or complementary services, represents a strategic opportunity. This article explores a project initiated by a telecom operator aimed at maximizing customer value while improving satisfaction through better-tailored offers. By leveraging advanced data science techniques, this project seeks to overcome challenges related to identifying customers who could benefit from an upgraded offer.
Upsell Project: Challenges and Solutions
The operator faces several challenges, including difficulty in identifying high-potential upsell customers and a lack of personalization in current marketing campaigns. These shortcomings result in high costs and revenue erosion. To address these issues, our consultants proposed a structured approach based on the CRISP-DM model, enabling a better understanding of customer needs and optimizing the offer catalog.
Methodology Steps: A Structured Approach Using Advanced Data Science Techniques
To tackle these challenges, our experts applied a structured approach based on advanced data science techniques to optimize upsell opportunities for the client. The methodology follows the CRISP-DM* model, a standard for data mining and data science projects. This structured process, broken down into six key phases, was complemented by a strategy to redesign the offer catalog to correct inconsistencies responsible for revenue erosion:
- Business Understanding: Analysis of upsell objectives and marketing needs.
- Data Understanding: Exploration of customer data to identify target segments.
- Data Preparation: Secure integration of customer data.
- Data Modeling: Use of predictive models to target customers.
- Catalog Optimization: Redesigning the catalog to ensure consistency and uniformity.
- Model Evaluation: Model assessment through A/B testing.
- Deployment: Implementation of recommendations for effective targeting.
Short- and Long-Term Benefits for the Client
The upsell project delivered significant results. Customer retention improved, churn rate decreased by 31.4%, and ARPU increased by 97.6%. Optimized marketing campaigns allowed for more efficient resource allocation, while personalized offers enhanced the customer experience. Additionally, a better understanding of customer behavior now enables anticipation of future needs, maintaining a competitive edge in the market.
The redesign of the offer catalog, combined with a detailed analysis of product differences, ensured greater consistency in proposals. This eliminated opportunities for customers to exploit discrepancies to reduce costs, which could have impacted the company's profitability. Standardizing offers aligns the catalog with profitability objectives while making proposals more attractive to customers.
Sofrecom’s Contribution
By partnering with Sofrecom, the operator benefited from expertise in data science, upsell strategy optimization, and customer relationship management. Sofrecom experts also proposed a redesign of the offer catalog to ensure overall coherence and uniformity, preventing exploitable inconsistencies. Through this collaboration, the operator transforms upsell opportunities into sustainable growth drivers, strengthening its market position.
Conclusion
This upsell project highlights the importance of a structured, data-driven approach to revenue optimization. By overcoming challenges related to customer identification and offer personalization, the operator not only increased profitability but also enhanced customer satisfaction. Thanks to a data-oriented strategy, collaboration with Sofrecom has strengthened results and enabled the identification of additional revenue niches.
