Beneficios y resultados

Increased product activations, boosting revenue and enhancing customer engagement; Improved overall user experience, fostering greater customer loyalty and reducing churn; Detailed data insights allowed for more personalized marketing strategies and retention communications

40% increase in product activations, leading to significant revenue protection

Antecedentes

NaranjaX is a fintech company based in Argentina that focuses on providing comprehensive financial services through digital platforms. Originally a major credit card issuer, it has evolved into a fintech leader with a strong emphasis on customer-centric practices, leveraging modern technology for product development and data security. The company uses innovative team structures such as "Squads" and "Tribal Squads" to enhance collaboration and agility in its operations. NaranjaX is recognized for its strategic use of cybersecurity measures to protect user data and improve service delivery.

Desafíos

Issue Identification: NaranjaX faced the challenge of identifying which customers were most likely not to activate their products within the next three months; Issue Impact: The challenge led to ineffective retention communications and proactive actions to enable product activations, resulting in significant revenue loss from existing customers

Solución

NowVertical's Role: NowVertical developed a comprehensive customer view by integrating demographic, geographic, and historical product usage data, including personal and contact information and details from central banks, insurance, and other business interactions. This integrated customer view served as the groundwork for constructing a data science-driven propensity model aimed at predicting product activation. This model was instrumental in identifying customers likely to disengage, enabling targeted interventions to decrease customer churn

Implementación

Data Analysis: Commenced with an in-depth analysis of customer processes and the existing technical data landscape; Data Modeling: Conducted a rigorous data modeling exercise aligned with NaranjaX's commitment to customer-centric solutions; Machine Learning: Developed a machine learning model using logistic regression and ML components (AWS + GCP) to calculate the likelihood of product activation for each customer