Dennis Henrique Ribeiro - Portfolio Page
Impulsionando o Crescimento Empresarial por meio de Operações Estratégicas

Dennis Henrique Ribeiro – Professional Portfolio
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Instant Messaging Solution for Delayed Orders
Project Overview
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➤ Category
Systems, Process & Digital Optimization
➤ Main KPIs (Acceptance Criteria)
[ • ] NPS impact
[ • ] Reduction of returns
• [SITUATION]:
In the previous process for handling delayed e-commerce orders (beyond eight days), the default procedure was automatic cancellation and return. This often caused frustration among customers who, despite the delay, would have preferred to continue waiting rather than have their orders canceled without consultation.
This practice directly impacted customer satisfaction and negatively affected the Net Promoter Score (NPS).
• [TASK]:
The challenge was to design and implement a solution that empowered customers to decide whether they wished to continue waiting for their delivery or cancel the order and receive a refund. At the same time, the solution needed to be automated to minimize manual rework and generate actionable insights into customer behavior.
• [ACTION]:
To address this, I first validated the concept with key stakeholders across Customer Service, IT, and the tracking operations team. I then modeled a simple and transparent conversational flow via WhatsApp, ensuring an intuitive customer experience. In parallel, I coordinated the definition of the system architecture, integrating the Transportation Management System with cloud infrastructure and a messaging platform for automated communication and response tracking. Once aligned, I led the development team through configuration and testing into the production environment.
• [RESULT]:
In a controlled production environment, where results were closely monitored to ensure stability and user adoption, it significantly reduced customer dissatisfaction, as approximately 50 customers per day could actively choose how to proceed with their delayed orders.
The pilot also generated valuable insights into consumer behavior in late-delivery scenarios that served as the foundation for future scalability and policy improvement.



