Problem
Lob, a leader in direct mail automation, sought to reduce postage costs for its customers. The company recognized that postage prices fluctuate based on various factors, and identifying the optimal times to purchase postage could lead to significant savings. However, predicting these optimal purchasing times required analyzing complex, real-time data, which was beyond their existing capabilities.
Additionally, Lob aimed to improve delivery efficiency by minimizing the distance between the source of postage pricing and customer demand. This necessitated a sophisticated approach to geographical data analysis and clustering, further complicating their operational processes.
Solution
To address these challenges, Lob partnered with Zams to leverage their advanced predictive analytics and machine learning capabilities. By integrating Zams' API, Lob accessed live streaming data from their pricing ecosystem, enabling real-time analysis of postage price fluctuations. Zams implemented over 30 predictive rules to determine the optimal times for purchasing postage, ensuring cost-effectiveness for Lob's customers.
Furthermore, Zams developed a geographical clustering algorithm tailored to Lob's needs. This algorithm analyzed the geographical distribution of customer demand and optimized the sourcing of postage pricing, effectively reducing the distance between the source and the demand points. This optimization not only decreased delivery times but also contributed to additional cost savings.
Outcome
Through the integration of Zams' predictive analytics and geographical clustering solutions, Lob successfully reduced postage costs for its customers. The implementation of over 30 predictive rules allowed Lob to purchase postage at optimal times, leading to significant cost savings.
The geographical clustering algorithm enhanced delivery efficiency by minimizing the distance between the source of postage pricing and customer demand. This improvement resulted in faster delivery times and increased customer satisfaction, reinforcing Lob's position as a leader in direct mail automation.
