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7 minute read
Telling a customer their order will arrive "in 3–5 business days" is not a delivery promise, it is an admission of uncertainty and it costs e-commerce brands more than most realise. Today, ShippyPro introduces Delivery Prediction: a machine learning engine that calculates the exact delivery date of any shipment, before the order is even placed. For the first time, brands using ShippyPro can give customers the same confident, precise delivery date that was previously reserved for the largest retailers with proprietary logistics data.
Built on hundreds of millions of real shipments processed through the ShippyPro platform, the model learns from how deliveries actually happen, across carriers, routes, countries, and time. It is not a carrier estimate dressed up as a prediction. It is a genuine machine learning model, already live in beta and rolling out to all customers and products shortly, with API access coming next.
🗝 Key Takeaways
- Exact dates, not ranges: Delivery Prediction replaces vague "3–5 business day" windows with a specific predicted delivery date, calculated before the order ships.
- Real data, real accuracy: The model is trained on hundreds of millions of actual ShippyPro shipments, not on carrier-supplied SLAs or static rules.
- Predictions update in transit: As a shipment moves, the model continuously recalculates the delivery date to reflect what is actually happening, including early detection of likely delays.
- One engine, multiple use cases: From checkout conversion to automated carrier selection to proactive customer communication, Delivery Prediction opens new possibilities across the entire order journey.
📋 In this article
Why Vague Delivery Windows Are Costing You Sales
The expectation gap
Shoppers have become accustomed to precision in almost every part of digital life. Research by the Baymard Institute consistently identifies unclear delivery timelines as one of the top reasons shoppers abandon checkout. When a customer asks "when will this arrive?" and the best answer is a five-day window, a portion of them simply leave.
What customers actually want at checkout
Consumers now benchmark against the delivery experience offered by the largest platforms, and bring those expectations to every purchase. An accurate delivery date at checkout is no longer a premium feature but a basic conversion requirement. Consumer research consistently identifies delivery certainty as a primary driver of online purchase confidence across all markets.
"Estimated delivery: 3–5 business days." Customer uncertainty at checkout. Higher cart abandonment, more WISMO tickets, and no way to handle delays proactively.
"Arrives Thursday, June 5." Precise date set before the order ships. Lower abandonment, higher customer trust, and automated communication the moment anything changes.
| Metric | Vague delivery window | Precise delivery date |
|---|---|---|
| Checkout conversion | Lower — uncertainty creates hesitation | Higher — customers commit when they know exactly when to expect delivery |
| WISMO contact volume | High — customers contact support to ask | Lower — the date is already communicated and updated throughout transit |
| Repeat purchase rate | Reduced — unmet expectations erode trust | Higher — consistent accuracy builds the loyalty that drives returning customers |
| Carrier selection quality | Manual or rule-based, often suboptimal | Data-backed — automatically pick the carrier most likely to deliver on time |
How ShippyPro Delivery Prediction Works
Trained on hundreds of millions of real shipments
Delivery Prediction is built on the full volume of shipments processed through ShippyPro over years of operation. This is not a generic model trained on publicly available data or built on carrier SLAs. It learns from actual delivery outcomes: how long each carrier really takes on each route, how performance varies by day of week, time of year and destination zone, and how those patterns shift over time. Every prediction reflects what the data says will happen not what a carrier promises.
The model receives order details — origin, destination, carrier, service type, and order timing — before the shipment is created or a label is printed.
Carrier historical performance, route behaviour, current network conditions, timing, and external signals are all weighted to build an accurate, shipment-specific prediction.
A single date — not a range — is generated. This can be surfaced to the customer at checkout, used in shipping notifications, or passed to automated workflows.
As the shipment moves, the model re-evaluates and updates the predicted date to reflect real conditions. Deviations are flagged early — often before a delay becomes visible to the customer.
Continuous updates throughout transit
A prediction set at label generation and never revised quickly becomes inaccurate. ShippyPro's model continues to evaluate each shipment as it moves, integrating live tracking data to refine the estimated arrival date in real time. If a shipment is running ahead of schedule or falling behind, the prediction reflects that giving your team time to act before customers need to ask.
| Factor | What the model learns from it |
|---|---|
| Carrier performance history | Actual on-time rates per carrier per route, not SLA promises |
| Route behaviour | How long specific origin-to-destination combinations actually take |
| Order timing | Day of week, time of day, proximity to peak periods and public holidays |
| External conditions | Network disruptions, seasonal congestion, and known service variations |
| Live shipment events | Real-time tracking updates that refine the prediction as the parcel moves |
What ShippyPro Delivery Prediction Unlocks Across the Order Journey
At checkout
Delivery Prediction gives brands the ability to display a specific delivery date before an order is placed, not a carrier's generic SLA, but a date the data actually supports. Shown at the right moment in checkout, this reduces the uncertainty that drives abandonment and sets accurate expectations from day one. It integrates directly with ShippyPro's AI shipping automation to make carrier selection a data-backed decision, routing each order to the carrier most likely to hit the predicted date for that specific shipment and route.
After the order is placed
Once an order ships, the predicted delivery date flows through to branded tracking pages and automated shipping notifications, keeping customers informed with accurate, continuously updated information rather than static carrier copy. This reduces WISMO (Where Is My Order) contacts — one of the largest drivers of post-purchase support costs — and gives customers a reason to trust the brand, not just the carrier.
When something is about to go wrong
Delivery Prediction can detect when a shipment is deviating from its expected path, often before the delay becomes visible in the carrier's tracking data. This gives operations teams, working within ShippyPro's Optimizer, the ability to act earlier: proactively communicating with affected customers, triggering re-ship or return workflows where needed, and preventing individual exceptions from becoming support tickets at scale.
ShippyPro's Delivery Prediction is currently running in beta within the ShippyPro platform. Full availability across all products and API access are coming shortly. If you are already a ShippyPro customer, contact your account manager to find out when you will gain access to your account.
Once Delivery Prediction is live on your account, combine it with ShippyPro automation rules to automatically route each shipment to the carrier statistically most likely to deliver on the promised date for that specific route and service. This turns a prediction into a live operational decision — with no manual intervention required.
Want to go deeper on data-driven delivery dates?
Read our full guide on how predictive delivery data reshapes checkout conversion, customer trust, and post-purchase experience.
Read more →The Foundation for Everything Coming Next
Already live in beta
Delivery Prediction is not a roadmap item. It is already running inside the ShippyPro platform in beta, processing real shipments and generating real predictions. It will become available to all customers and across all ShippyPro products in the coming weeks, with API access enabling merchants to surface predictions inside their own storefronts, checkout flows, and customer-facing tools following shortly after. Full documentation will be available through the ShippyPro API Documentation.
The first model in a growing AI layer
Delivery Prediction is the first machine learning model ShippyPro has built. It is also, by design, a foundation. The same data and infrastructure that powers delivery date prediction will underpin future capabilities, a growing AI layer that will progressively improve and automate more of the decisions involved in moving an order from warehouse to door.
It joins a set of AI capabilities already available on the platform: Optimizer, which gives teams full visibility into distribution performance and costs; Automation, which builds intelligent shipping workflows that act at scale and Carrier Invoice Analysis, which identifies refund-eligible billing errors at an accuracy no manual review process can match. Delivery Prediction is the next step and the start of something bigger.
AI Shipping Automation
Build intelligent workflows that select carriers, trigger communications, and act at scale — without any manual intervention.
Explore Automation →Optimizer
Track exception rates, delivery performance, and shipping costs across all your carriers. Continuously improve your distribution operations.
Explore Optimizer →Track & Trace
Real-time shipment visibility across every carrier, powering proactive customer communication and faster exception resolution.
Explore Track & Trace →ShippyPro Resources
Guides, webinars, and research to help you get the most from your shipping operations — from carrier setup to advanced automation.
Browse Resources →Shipping Notifications
Keep customers informed at every step with automated, branded shipping notifications — now powered by accurate predicted delivery dates.
Learn More →Start Your Free Trial
Try ShippyPro free for 14 days — no credit card required. Connect your store, your carriers, and start shipping smarter today.
Get Started →What is ShippyPro Delivery Prediction?
ShippyPro Delivery Prediction is a machine learning engine that calculates the exact expected delivery date of a shipment before the order is shipped — or even before it is placed. Unlike carrier-supplied ETAs, it is trained on hundreds of millions of real ShippyPro shipments and accounts for carrier performance history, route behaviour, timing, and external conditions to generate a precise, single-date prediction rather than a vague range.
How is Delivery Prediction different from a carrier's estimated delivery time?
Carrier ETAs are generic SLAs: they reflect what a carrier aims to achieve under normal conditions, not what actually happens on a specific route at a specific time. ShippyPro's Delivery Prediction is built on actual delivery outcomes across all carriers processed through ShippyPro — learning from real performance variability over time. It also updates continuously as the shipment moves, which carrier ETAs do not.
When will Delivery Prediction be available to all customers?
Delivery Prediction is currently in beta within the ShippyPro platform and will be available to all customers across all ShippyPro products in the coming weeks. API access — allowing merchants to surface predictions in their own storefronts and checkout flows — is planned to follow shortly after general availability.
Can I use Delivery Prediction to automate carrier selection?
Yes. Once live on your account, Delivery Prediction works in combination with ShippyPro's automation rules to route each shipment to the carrier statistically most likely to hit the predicted delivery date for that specific origin, destination, and service type. You can configure this directly within the ShippyPro AI Automation settings, turning a prediction into a live operational decision without any manual step.
Start shipping with prediction-backed confidence.
Connect your store to ShippyPro and give your customers the delivery dates they deserve — before the order even ships.
Andrea Gaspari is a Product Designer at ShippyPro. He designs user-centered experiences that turn shipping data into actionable insights and help merchants streamline operations, enhance delivery performance, and optimize carrier selection. Andrea is passionate about simplifying complexity through thoughtful design and building tools that empower eCommerce teams to make confident, data-backed decisions.