Since launching Grasshopper in 2014, we have gathered large amounts of data on the products handled over the hundreds of thousands of deliveries that have been processed through our platform. We have seen what works and what doesn’t – which products cause more issues for delivery teams, which products take up more space on delivery trucks, and much more. We are leveraging this product data to gain valuable insights into the products passing through the Deliveright Network, in the hopes of making the delivery experience better for our customers and our delivery partners.
After months of research and development, we are excited to launch our machine learning algorithm, Grasshopper Product Insights (GPI). GPI will enable our users to be much more informed about what works and what doesn’t when delivering, based on a data-centric approach. Here are few highlights:
- Accurate Data – GPI will help customers provide accurate and consistent data for their orders (weights, SKUs, dimensions, etc.), letting them process their orders much faster. It will do this through predictive modeling, pulling from our extensive database of prior deliveries to find comparable orders.
- Truck & Capacity Management – Using GPI, Grasshopper will manage truck capacity much better, improving route optimization and truck utilization by seeing what has worked and what hasn’t in past deliveries.
- Risk Assessment – GPI provides real-time risk assessment on every product, allowing the shipper to assess any given order’s potential for damage, special product handling needs, and much more.
- Learning, Non-Stop – GPI’s machine learning algorithm will be an ongoing learning process, adjusting recommendations based on incoming data, which will improve decision-making as more products are processed.
We look forward to hearing your feedback about GPI! Please send us any ideas to make GPI even better.