From Tracking to Insight: How Carriyo Intelligence Surfaces Revenue at Risk and Carrier Performance
Every shipment a brand sends generates a stream of events: booked, picked, packed, shipped, in transit, out for delivery, delivered — or delayed, failed, returned. Multiply that by thousands of orders a day across multiple carriers, and most eCommerce operations teams are sitting on millions of data points about their own delivery performance.
Almost none of it becomes a decision.
The typical operations dashboard counts things: shipments in transit, deliveries today, open tickets. What it does not say is which carrier is quietly missing its promise in one region, which SLAs are about to breach, and — most importantly — how much revenue is currently tied up in orders that are late, stuck, failed, or heading back to the warehouse. Teams discover delivery failures the same way their customers do: after the fact, one support ticket at a time.
Carriyo Intelligence — the new analytics layer of Carriyo, The Intelligent Commerce Platform, launching in Q4 2026 — is built to close that gap. It turns the shipment data the platform already captures into carrier scorecards, SLA monitoring, and a running answer to the question every operator and finance leader actually cares about: how much money is at risk right now, and where?
The Problem: Data-Rich, Insight-Poor
Delivery data has a peculiar failure mode. There is too much of it to read and too little of it in a form anyone can act on. Carrier portals each report performance their own way. Spreadsheet reconciliations arrive weeks after the period they describe. And the metrics that do get tracked are usually operational counts — shipments, scans, tickets — rather than commercial outcomes.
The cost of that blind spot is not hypothetical. Loqate's "Fixing Failed Deliveries" study found that 8% of domestic first-time deliveries fail, costing retailers an average of $17.20 per order [1]. And the downstream damage compounds: in a FarEye consumer survey, 85% of respondents said they will not shop with a retailer again after a poor delivery experience [2]. A late or failed delivery is not just an operational exception — it is revenue already earned, now back in jeopardy, along with the customer attached to it.
The fix is not more dashboards. It is analytics that connect delivery events to the two things a business runs on: performance and money.
Carrier Performance: From Anecdotes to Scorecards
Ask an operations team which of their carriers is best and the answer is usually a feeling. Carriyo Intelligence replaces the feeling with a benchmark.
Because Carriyo sits across every carrier a brand uses — the platform integrates with 100+ carriers — it sees every shipment through a single, normalized lens. That makes true side-by-side comparison possible:
- On-time delivery rate — measured against the promise, not the average.
- First-attempt success rate — the single biggest driver of failed-delivery cost.
- Average transit time — by carrier, region, and service level.
- Cost per delivery and cost efficiency — so speed is always weighed against spend.
- Exception and damage rates — how often things go wrong, and how badly.
- Customer satisfaction — post-delivery feedback tied back to the carrier that delivered.
The benchmarking works across regions and service levels, which is where it earns its keep. A carrier can look excellent nationally and be your worst performer in one city. Surface that pattern, and the response is straightforward: shift allocation, renegotiate with evidence, or set business rules that route around the weakness. Without the data, the same pattern just shows up as unexplained churn in one postcode.
SLA Adherence: Monitor the Promise, Not Just the Package
Tracking tells you where a package is. SLA monitoring tells you whether you are keeping your word.
Carriyo lets teams define and monitor SLAs across the entire post-checkout lifecycle — from fulfillment through delivery and returns — with automated alerts when thresholds are at risk. That last phrase matters: at risk, not breached. An SLA report that arrives at month-end is an autopsy. An alert that fires while the shipment can still be rescued is an intervention.
In practice, this changes the shape of the operations day. Instead of scanning lists of in-transit shipments, teams work from a prioritized view of promises in danger — the orders where the gap between commitment and reality is opening up, ranked by how much it matters.
Revenue at Risk: The Number That Changes the Meeting
This is the capability that moves delivery analytics out of the ops room and into the leadership meeting.
Carriyo Intelligence quantifies revenue at risk throughout the day: the total order value currently jeopardized by delivery problems, expressed as a monetary figure, as a share of GMV, and as a trend over time. Rather than one undifferentiated number, the risk is broken into the distinct situations that create it:
- Delayed shipments — orders still in transit past their promised delivery date.
- Failed deliveries — orders where a delivery attempt failed today and the next attempt will decide the outcome.
- Stuck fulfillment — orders sitting unfulfilled in the warehouse queue beyond their processing threshold.
- Pending returns — approved and in-progress returns representing live refund liability.
- Churn-risk customers — customers whose recent delivery experience earned negative feedback, weighted by their value to the business.
Each category carries a value and a count, and each drills through to the actual orders behind it. That drill-through is the difference between a vanity metric and a work queue: a team can go from "delayed shipments are our largest risk category this week" to the specific orders, carriers, and destinations driving it — and act on them in the same platform that manages the shipments.
The framing is deliberate. "1,200 delayed shipments" is a status. "Six figures of revenue sitting in shipments past their promised date, trending up over 30 days" is a decision-forcing statement — one that finance, operations, and customer experience can all read the same way.
See It Coming: Prediction and Proactive Alerts
Surfacing today's risk is table stakes. The larger prize is shrinking tomorrow's.
Carriyo's predictive analytics use AI to flag delivery delays, carrier capacity issues, and demand surges before they become failures. Combined with the centralized exception queue — delayed shipments, failed deliveries, and stuck orders in one prioritized workflow instead of scattered across carrier portals — the operating posture flips from reactive to preemptive. The team works the risk before the customer feels it.
And like everything in Carriyo, the analytics layer scales with the team's maturity: monitor manually, automate with rules-based alerts, or let AI-powered anomaly detection watch the data and surface optimization recommendations. Custom reports, scheduled exports, BI-tool integration, and API access to all analytics data mean the numbers also flow wherever the business already does its thinking.
What This Changes for the Business
The outcomes compound across three fronts:
- Fewer write-offs. When failed and at-risk deliveries are surfaced while intervention is still possible, a meaningful share of the $17.20-per-failure cost [1] becomes avoidable rather than absorbed.
- Protected repeat revenue. With 85% of consumers saying one poor delivery experience is enough to lose them [2], catching the late order before the customer does is retention work — arguably the highest-leverage kind.
- Stronger carrier economics. Allocation decisions and rate negotiations backed by normalized, cross-carrier performance data consistently beat decisions backed by anecdote.
This is analytics built on real operating scale: Carriyo tracks over $5B in GMV and more than 20 million shipments for 100+ brands, across 100+ carriers and 200 countries. The intelligence layer is not bolted onto the shipping platform — it is the shipping platform, looking at its own data with commercial intent.
The Bottom Line
Tracking answers "where is the package?" Intelligence answers the questions that actually run the business: Which carriers are keeping their promises? Which promises are about to break? And how much revenue is riding on the answer?
Carriyo Intelligence turns the exhaust of everyday shipping into carrier scorecards, SLA foresight, and a live, money-denominated view of delivery risk — so the first person to know about a problem is your team, not your customer.
Carriyo Intelligence launches in Q4 2026. From checkout to doorstep, with the numbers to prove it. Book a demo and ask about early access ahead of the launch.
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Sources
1. Loqate (a GBG solution). "Fixing Failed Deliveries 2021: Stamping Out Faulty Fulfillment" (study of 304 retail executives and 3,040 consumers in the US, UK, and Germany, conducted December 2020) — 8% of domestic first-time deliveries fail, costing retailers an average of $17.20 per order. https://www.prnewswire.com/news-releases/as-ecommerce-thrives-new-loqate-study-reveals-the-cost-of-failed-deliveries-301240263.html 2. FarEye. Consumer survey of ~1,000 US consumers (June 2022) — 85% of respondents said they will not shop with a retailer again after a poor delivery experience. https://fareye.com/news/survey-reveals-perils-of-poor-delivery-experience