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Remove package delivery time uncertainty. Reduce customer service costs. Recover from missed promises.
Start showing your shoppers a delivery promise on product pages to build trust and reduce uncertainty over delivery times. Showing shipping speed (e.g. 3-7 days) is far less effective. Adding an estimated time of arrival is a super simple way to encourage customers to start a cart.
Increase checkout conversions and reduce cart abandonment with data-driven estimated package delivery times. Have multiple delivery options? Display unique dates for each carrier with a machine learning model and unique algorithm that accounts for delivery methods, carrier service levels, holidays, past performance, and trending data.
The parcelLab delivery date promise is based on the full package journey – order to door. A poor estimate can lead to a bad customer experience so it’s critical to calculate datapoints from article origin to warehouse or store operating hours to processing and handling times and carrier pick-up windows. You can generate higher satisfaction and further reduce “Where is my order” services calls with a data driven forecast combined with proactive status notifications.
Even with the best intentions, things don’t always go to plan. Prepare for these moments and save valuable customers from bad experiences that lead to churn. Monitor production, processing, packaging, pickup and delivery steps so you’ll know right away if a delivery promise is at risk. Create special communications flows to keep customers informed of progress and offer incentives like free shipping on next order if promises are missed. Build confidence to keep customers coming back.
If no address is available when viewing product pages, location detection will be used to display estimates for the region.
Constantly updates estimated package delivery time based on real-world trending and patterns across brands and carriers.
Display delivery date promises in your app with a simple API.
Set and update attributes like holidays, warehouse operational hours, packing or courier pickup times.
Considers your distribution setup, item origin, customs timeframe, and multiple carrier requirements for better package delivery predictions.
Get a forecast that accounts for order to door, not just carrier commitments.