The Challenge
One of the largest US-based global logistics providers delivers over 14 million packages across 220 countries daily. Historically, one of the more complicated aspects of international shipping is customs clearance, but this company is using data and analytics to turn this into a market differentiator and a game-changer in the International Express segment.
The Solution
The solution required building a big data environment for analytical modeling that scales up to enterprise needs, adheres to industry standards and involves agile delivery teams. Today, the company has their first models into production with the first iteration of the analytics architecture, and a dozen new models in development coinciding with the next iteration of the analytics architecture this year. The company expects the data science development to scale up in the coming years to handle over 100 models.
The Results
The client saw significant improvement in B2C and B2B customer experience navigating the multitude of forms required to ship a parcel internationally (e.g. CSat, Net Promoter, etc.), achieved 94-97% customs clearance success rate (i.e. parcels are not caged, delayed or returned to send by customs), and 35-45% reduction in current manual efforts required to address parcel caging risk by customs.