Predictive Delivery Dates
Set and satisfy delivery expectations
Leverage our eCommerce Predictive Delivery Dates machine learning model, refined from over 26 billion shipment events. Access a delivery promise date that will help your shoppers make faster, more confident decisions on the checkout page.
Drive more sales
When given an “earliest delivery date” rather than a “ships by” date, customers are 55% more likely to make a purchase.
Decrease cart abandonment rate
41% of customers abandon their online carts due to a mismatch in delivery date expectations.
Boost customer satisfaction
Consumers consider delivery date reliability their primary concern after price when selecting an online retailer.
With project44, we’ve got a unified experience that feels like it’s all coming from UncommonGoods regardless of carrier. We see the delivery date as a promise, and the project44 platform is key to us being able to keep it.
MC Halfpenny
Director of Operations
Uncommon Goods
How it works
01
Increase delivery accuracy
With machine learning models developed from 26 billion shipment events, eCommerce Predictive Delivery Dates achieve up to 60% higher accuracy compared to carriers.
02
Multiple date estimates
Choose between two dates estimation options to present to customers. An aggressive model aims to maximize accuracy while the conservative model aims to minimize late errors.
03
Automate risk analysis
Our models maintain a middle ground between over and under-promises, giving shippers a clear view of risks to their delivery accuracy.
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Consumer Visibility
Keep end consumers more informed and engaged with real-time visibility of last-mile shipments on tailored branded tracking pages with personalized delivery alerts.
Last Mile Resolution
Enhance customer experience with a dedicated management hub that highlights distressed shipments within your network with self-service resolution options.
Last Mile Insights
Access essential analytics and metrics on carrier and shipment performance, empowering your team to tackle the most important delivery issues.
