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Introducing Estimate: accurate delivery dates that convert shoppers and cut costs

Powered by machine learning trained on millions of real shipments, so you can promise a delivery date and back it up.

Estimate is a machine learning-powered API that predicts delivery dates with ≥90% accuracy. It gives businesses a reliable date to show at checkout, trained on real delivery outcomes from millions of shipments, not carrier-stated transit times. One API call returns a date your shoppers can trust, along with the cheapest way to keep it.

Why delivery uncertainty is costing you more than you think

75%

of shoppers say putting an estimated delivery date on the product page or in the cart positively influences their decision to buy. [1]

85%

of Shippo merchants shipping 100+ labels a month had at least one order that could have cost less to ship and arrived just as soon — or sooner. [2]

Sources: [1] thegood.com, [2] Shippo platform data, July 2026

Delivery uncertainty costs you twice: the sales you don't win, and the shipping you overpay for.

The problem is that most delivery date tools rely on carrier-stated transit times, which are the carrier's published best-case scenario. Those estimates don't account for the things that actually affect delivery, including weather events, hub congestion, seasonal surges, and carrier performance that varies by route, day of week, and time of year. The result is a date you can't stand behind, so most businesses don't show one at all.

How Estimate works

Step 1: Send the details

Your engineering team makes a single API call with origin ZIP, destination ZIP, and package dimensions. Set a maximum acceptable delivery date, and Estimate will filter out anything that can't meet it.

Step 2: Run the prediction

Our machine learning model returns an estimated delivery date at the confidence level you set. The model accounts for seasonal carrier performance, U.S. holidays, and route-level variance. For routes with limited shipping history, it automatically falls back through a hierarchy of backup models and tells you which source was used in the response.

Step 3: Show it where it matters

Display the date to shoppers as a single date ("Arrives Nov 22") or a date range ("Arrives Nov 21–23") on product pages, at checkout, or both. Or use the prediction to inform carrier selection, finding the cheapest option that meets your delivery promise before you buy the label.

How to use Estimate across your business

Win shoppers before they hesitate

The product page is where doubt lives. A shopper sees something they want but without knowing when it will arrive, they hesitate, and hesitation is where you lose the add-to-cart.

Estimate lets you surface a real delivery date at the product page level, before a shopper ever reaches checkout. The result is a date they can plan around: "Arrives November 22" instead of "ships in 3–5 business days."

Convert more sales at checkout

Checkout is where delivery uncertainty does the most damage. When shoppers see vague ranges or no date at all, they're being asked to make a buying decision with incomplete information. Many don't.

Estimate makes the choice concrete. "Arrives Nov 22 for $8.99 or Arrives Nov 24 for free" gives shoppers everything they need to decide. Standard vs. Expedited leaves them guessing.

Cut shipping costs without cutting corners

Most businesses pick carriers out of habit or rule-of-thumb, and overpay as a result.

What we found in July 2026: Cheaper usually doesn't mean slower

Across Shippo's platform, 85% of merchants shipping 100+ labels a month had at least one order that could have cost less to ship and arrived just as soon — or sooner. When a cheaper option existed, it was 22% cheaper on average, or $5.26 less per label. And here's the part that surprised us: in 44% of those cases, the cheaper option was scheduled to arrive sooner than what the merchant actually bought.

85%

of Shippo merchants shipping 100+ labels a month had at least one order that could have cost less to ship and arrived just as soon — or sooner.

22%

cheaper on average when a cheaper option existed, or $5.26 less per label.

44%

of those cases, the cheaper option was also scheduled to arrive sooner than the one the merchant bought.

Source: Shippo platform data, July 2026. Comparisons use estimated delivery dates modeled at p75 transit; savings are potential, not realized.

That changes what kind of problem this is. If picking the wrong rate only ever cost you money, a spreadsheet and a rule of thumb would mostly handle it. But when the cheaper option is also the faster one nearly half the time, there's no rule of thumb to apply. The answer depends on the carrier, the lane, the service level, and the week. It's a prediction problem.

That's the case for putting a model on it. Estimate checks every carrier and service level against the date you need to hit, then keeps only the options that qualify, so the cheapest one that still makes your promise is the one you see.

Protect time-critical deliveries

For some shipments, the delivery date is not a nice-to-have. Cold-chain pharmaceuticals need to arrive before temperature tolerance is exceeded. Event-driven goods need to arrive before the event. And perishables have a hard deadline.

Set the confidence level to High (p95) and pass a maximum acceptable delivery date. Estimate filters out every carrier and service level that can't meet the window. You only see options you can stand behind, and you know before buying the label, not after.

What makes Estimate different

Built on one of the largest shipping datasets in ecommerce

Carrier-stated transit times are optimistic by design. They reflect ideal conditions, not the real-world variability that determines whether your package actually arrives when expected.

Estimate is trained on actual delivery outcomes across millions of shipments, including real performance by route, day of week, seasonal pattern, and carrier network. The model accounts for things carriers don't publish: hub congestion, weather impact history, and holiday handling variation by service level.

Accurate enough to actually show

Basic EDD tools are built on transit time tables with a confidence interval wide enough to be useless in a checkout UI. Estimate targets ≥90% window accuracy, meaning the actual delivery date falls within the predicted window for 9 out of 10 shipments. That's a number you can put in front of shoppers.

And it comes from a track record. 93% of businesses using Estimate say it helps them choose the best service level. 81% feel more confident about when their shipments will arrive.

Live in a sprint, not six months

Enterprise EDD platforms require lengthy implementation timelines and custom contracts. Estimate is a single endpoint with SDK support in Python, Ruby, JavaScript/Node.js, and PHP. Your team can go from zero to live in a single sprint. Use the interactive API explorer in our docs to try requests before writing a single line of integration code.

Frequently asked questions about Shippo Estimate

Who is Shippo Estimate for?

Businesses shipping 1K to 500K orders per month who have an engineering team (or technical agency support) and are losing sales to delivery uncertainty or relying on EDD tools that aren't accurate enough to make real promises on.

How accurate are the predictions?

Our predictions are built on actual delivery outcomes, not carrier-stated transit times, so they account for real-world variability like weather, hub congestion, and seasonal surges. Accuracy varies by confidence level:

  • Basic (p50): 50% accuracy threshold — a precise median estimate.
  • Default (p75): 75% accuracy threshold — a more reliable window.
  • High (p95): 95% accuracy threshold — for time-critical shipments.
How are Shippo Estimate dates displayed?

The API returns a date you format for your UI. Display it as a single date ("Arrives Nov 22") or a date range ("Arrives Nov 21–23"). The display format is your call. Shippo Estimate returns the data.

What's the difference between confidence levels?

There are three, each representing a different accuracy threshold. Basic targets 50%, a precise median estimate. Default targets 75%, a more reliable window for when timing matters more. High targets 95%, for situations where missing the window isn't an option, including perishables, event goods, pharmaceuticals, and medical deliveries.

Which carriers and service levels are supported?

At launch, Shippo Estimate covers most domestic U.S. service levels, including USPS, UPS, FedEx, LaserShip, OnTrac, AxleHire, and Veho. Supported service levels include USPS Ground Advantage, USPS Priority, USPS Priority Express, USPS Media Mail, UPS Ground, UPS Ground Saver, UPS SurePost, UPS 3 Day Select, UPS Second Day Air, UPS Next Day Air, UPS Next Day Air Saver, UPS Next Day Air Early AM, FedEx Home Delivery, FedEx Ground, FedEx Ground Economy, FedEx Smart Post, FedEx 2 Day, FedEx 2 Day AM, FedEx Express Saver, FedEx Standard Overnight, FedEx Priority Overnight, FedEx First Overnight, LaserShip Ground, OnTrac Ground, AxleHire Next Day, Veho Premium Economy, Veho Ground Plus, and Veho Next Day.

What happens for routes with limited shipping history?

Shippo Estimate always returns a response. For routes where the primary model has limited data, it automatically works through a hierarchy of backup models, and the response tells you which source was used.

Do I need to be a developer to use Shippo Estimate?

The API is built for teams with engineering resources. No developer resources right now? On the Pro Plan in the Shippo web app, you'll still see accurate estimated delivery dates powered by Estimate next to your rates every time you buy a label, so you stop paying for speed you don't need. The API is what lets you show those dates to your shoppers, on your product page and at checkout.

Start adding delivery dates that convert shoppers and cut costs

Estimate is available now for API customers.

Contact an expert or explore the API docs to see how the integration works.

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