According to recent statistics, nearly half a billion people across the Americas shop online every year. With that kind of volume, fast and reliable shipping isn’t just a nice-to-have, it’s essential. In Q2 2025, shipping across the Americas moved quickly, especially on domestic routes like those within the United States, Canada, and Mexico. However, when parcels crossed borders, delivery times and success rates started to vary. Some lanes ran smoothly, while others faced delays, missed first attempts, or issues caused by either the carrier or the customer. But how were the Americas' e-commerce shipping benchmarks in Q2 2025?

Just like we saw in the European e-commerce shipping benchmarks Q2 2025, speed and reliability are no longer optional, they’re expected. Today’s e-commerce teams rely on smart tools like AI Decision Intelligence to track performance, spot problems early, and adjust delivery promises in real time. In this review of the Americas' e-commerce shipping benchmarks Q2 2025, we’ll break down key metrics like transit time, on-time delivery, first-attempt success, and issue ratio, and show how retailers and logistics teams can use this data through AI Decision Intelligence to improve customer experience and logistics operations.

The Americas’ Q2 2025 Delivery Landscape

In Q2 2025, delivery performance across the Americas showed strong results in major urban corridors, where transit times stayed fast and on-time ratios remained high. However, rural areas added complexity, with longer routes and fewer handovers slowing things down. Collection-point usage was widespread in the United States and Canada, thanks to strong infrastructure and tracked services from carriers like Canada Post. In contrast, LATAM markets saw lighter adoption, with hyper-local pickup models still emerging and not yet widely used.

What’s more, operational challenges varied by region. In the Southern Cone, several flight cancellations across Mexico and Argentina, supply chain issues, and weather-related disruptions led to more recipient-driven delays. Mexico faced a spike in carrier issues, driven by a transport strike at Manzanillo port and flight restrictions affecting cargo slots. 

On the innovation front, North America saw growth in nano-fulfillment centers and smarter AI routing, with Amazon opening its $500 million Oregon facility. Similarly, LATAM countries like Peru and Costa Rica expanded capacity with new infrastructure, such as the Port of Chancay and Jorge Chávez International Airport Expansion. These developments helped offset risks from global strikes and trade tensions, but also highlighted the need for flexible, data-driven delivery strategies across the region.

Top 5 Domestic Trade Lanes (Q2 2025)

United States to United States (US–US)

Benchmark: The US domestic lane showed solid performance in Q2 2025, with a mid-range average transit time of 2.95 days and a strong on-time delivery ratio of 98.5%. Collection point usage was exceptionally high at 63.29%, but dwell time reached 93.87%, indicating parcels often stayed really long after arrival.

What to Watch: Both carrier issues (3.2%) and recipient issues (1.1%) contributed to delivery friction. Scan quality must remain consistent to ensure visibility and reduce delays. 

Ops Tips: Retailers and e-commerce logistics providers should tailor delivery promises based on postcode density. This allows tighter windows in urban zones and a greater buffer in rural areas. Weekend cutoff adjustments can help manage peak demand. Promoting pickup options in high-dwell regions may improve first-attempt success and reduce strain on carriers.

Canada to Canada (CA–CA)

Benchmark: In Q2 2025, Canada’s domestic lane was fast and efficient, with an average transit time of 1.92 days and an on-time delivery ratio of 98.5%. In addition, the first-attempt delivery success was high at 92.97%, though issue ratios were elevated—carrier at 5.56% and recipient at 5.36%. 

What to Watch: Increased issue rates suggest challenges in both handover quality and customer readiness. Data spikes may indicate scan gaps or depot congestion. 

Ops Tips: Retailers and logistics carriers should optimize their regional carrier mix to reduce friction. Encouraging locker and PUDO usage in dense postcodes can ease last-mile strain. Sending ETA notifications and frequent updates via SMS or WhatsApp may help reduce missed deliveries and improve customer satisfaction.

Mexico to Mexico (MX–MX)

Benchmark: Mexico’s domestic lane was quite fast among the group, with a transit time of 1.69 days and a high FADS of 95.2%. On-time delivery was strong at 98.54%, but carrier issues were significantly high at 16.34%, the highest in this set. 

What to Watch: High carrier issue rates point to scan gaps, depot congestion, and inconsistent handovers. These factors may undermine delivery reliability. 

Ops Tips: Shipping companies and retailers should prioritize early-day handovers to improve delivery flexibility. Implementing SLA tiers by region can help align expectations with local conditions. Strengthening scan compliance and re-scan protocols will be critical to reducing blind spots and improving delivery performance.

Argentina to Argentina (AR–AR)

Benchmark: Argentina’s domestic lane had the shortest transit time at just 0.83 days, with a healthy FADS of 89.31%. Carrier issues were low at 0.52%, but recipient issues were high at 8.29%, indicating last-mile challenges. 

What to Watch: Poor address quality and unclear delivery instructions may be driving missed attempts. Delivery-window expectations also need better alignment. 

Ops Tips: Retailers and delivery companies should enforce address validation at checkout and provide clear apartment delivery guidance. Offering pickup options in dense urban areas can help reduce failed deliveries and improve overall success.

Chile to Chile (CL–CL)

Benchmark: Chile’s domestic lane was reasonably fast, with a transit time of 1.76 days and a strong first-attempt delivery success ratio of 92%. Carrier issues were notable at 7.96%, while recipient issues were nearly nonexistent at 0.01%. PUDO usage was extremely low at 0.26%, and dwell time was the lowest in the group at 33.33%. 

What to Watch: Missed handoffs and low contact rates may be contributing to increased carrier issues. Moreover, the lack of pickup options limits flexibility for shoppers. 

Ops Tips: Retailers should actively promote pickup options to reduce delivery strain. Proactive ETA messaging and reattempt scheduling can help improve first-attempt success and reduce delays caused by missed contact.

H2. Top 5 Cross-Border Trade Lanes (Q2 2025)

United States to Canada (US–CA)

Benchmark: During Q2 2025, the United States to Canada cross-border trade lane had a moderate transit time of 3.84 days and an on-time delivery ratio of 90.32%, which was lower than other US outbound lanes. First-attempt delivery success reached 89.43%. Issues were split between carriers (5.69%) and recipients (7.5%), while collection point usage remained modest at 4.91%. 

What to Watch: Linehaul timing and customs-adjacent delays continue to affect consistency. Border handovers and scan gaps may also contribute to missed expectations. 

Ops Tips: Retailers and shipping carriers should display EDD windows with milestone tracking to manage customer expectations. Localized notifications can also be adopted to help reduce confusion. Tightening cross-dock cutoffs may improve handover speed and reduce delays.

United States to United Kingdom (US–UK)

Benchmark: The US–UK trade route was faster than other long-haul exports, with an average transit time of 3.51 days and an impressive on-time delivery ratio of 98.78%. First-attempt delivery success was 81.17%, and issue ratios were moderate—carrier at 4.81% and recipient at 4.54%. 

What to Watch: Flight congestion during peak periods can affect promise accuracy. Missed first attempts may stem from unclear delivery instructions or timing mismatches. 

Ops Tips: E-commerce logistics carriers and retailers should offer late-cutoff services where feasible and ensure documentation is pre-cleared to avoid customs delays. Promoting pickup options in metro areas can help reduce failed deliveries and improve customer experience.

Canada to the United States (CA–US)

Benchmark: This lane performed exceptionally well, with an on-time delivery ratio of 98.78% and very low issue rates—carrier at 2.68% and recipient at 1.29%. Collection point usage was high at 38.04%, and dwell time reached 92.81%, indicating fast pickup after arrival. 

What to Watch: Border handoffs must maintain scan fidelity to preserve visibility and avoid delays. Addressing timing mismatches during cross-border scans can also help prevent false delay flags and improve customer confidence.

Ops Tips: Retailers should maintain early-day handover discipline to support carrier efficiency. Reinforcing locker and pickup defaults in dense postcodes can help sustain high first-attempt success and reduce last-mile strain.

United States to Australia (US–AU)

Benchmark: This was the longest lane in the set, with a transit time of 5.24 days. Despite the distance, on-time delivery was strong at 98.44%, and first-attempt delivery success reached 90.19%. Carrier and recipient issues were balanced at around 5.2% each, with moderate PUDO usage at 7.34%. 

What to Watch: Air capacity swings and weekend effects can disrupt delivery timelines. Unexpected customs holds and limited handover slots during off-peak hours can further compound delays on this lane.

Ops Tips: Retailers should use windowed estimated delivery dates (EDDs) to buffer against delays and send proactive communications when disruptions occur. Choosing services with reliable handoffs can help maintain consistency across long-haul routes.

United States to Germany (US–DE)

Benchmark: The United States to Germany cross-border trade lane had a long transit time of 5.05 days in Q2 2025. Also, the route recorded the lowest on-time delivery ratio in the group at 88.53%. First-attempt delivery success was 82.47%. Issue ratios were the highest among these lanes, with carrier at 6.45% and recipient at 12.66%. PUDO adoption was relatively high at 12.47%. 

What to Watch: Failed first attempts were often linked to unclear addresses or apartment delivery challenges. Import peaks also added pressure to the system. 

Ops Tips: Retailers should add delivery guidance at checkout to reduce confusion. Promoting pickup options can help improve success rates. Setting service level agreements (SLAs) based on stock-keeping unit (SKU) size and packaging type may also improve handling and reduce delays.

What This Means in AI Commerce

Why These Benchmarks Matter Now

In today’s AI-powered commerce landscape, delivery performance is no longer a backend concern. It’s a front-line factor in how products are discovered, ranked, and purchased. AI shopping agents and checkout copilots now assess reliability in real time. Thereby, influencing which merchants get surfaced and which ones get skipped. 

If you pad delivery promises too generously, conversion drops. If they’re too optimistic and fail, customer experience suffers. That’s why benchmarks like transit time, first-attempt delivery success, and issue ratios are critical. They directly shape how AI systems perceive and promote your store.

How AI Decision Intelligence Lifts Key Metrics (and What You Can Do)

AI Decision Intelligence is reshaping delivery performance by turning raw logistics data into actionable insights. It doesn’t just monitor, it adapts. By analyzing lane-level trends, recipient behavior, and carrier reliability, AI Decision Intelligence helps merchants, shipping carriers, and platforms fine-tune delivery promises, reduce friction, and improve customer satisfaction. Here is how AI Decision Intelligence drives impact across critical logistics performance metrics and what you can do to amplify those gains.

On-Time Delivery & Transit Time

AI Decision Intelligence improves delivery accuracy by generating postcode-level Estimated Delivery Dates (EDDs) and optimizing carrier and hub selection based on domestic or cross-border lane performance. It continuously back-tests delivery promises to ensure they reflect real-world conditions. 

On your end, this means setting micro-SLAs by lane and postcode, reviewing performance weekly, and adjusting cutoff times and delivery windows based on emerging trends. Together, these actions help maintain promise integrity and reduce missed expectations.

First-Attempt Delivery Success (FADS)

To improve first-attempt delivery success, AI refines promise accuracy, sends proactive delivery notifications, and recommends the most suitable delivery options, whether home, locker, or pickup point. Your role is to make those options visible and flexible at checkout, especially on lanes with historically low FADS. You can also experiment with pickup nudges through A/B testing and strengthen address capture fields to reduce failed attempts. Clear delivery guidance during checkout further supports successful outcomes.

Issue Ratio (Carrier & Recipient)

AI monitors scan gaps and delay patterns using Focus Alerts, then recommends targeted fixes based on the root cause. These alerts help pinpoint whether issues stem from carrier performance, recipient behavior, or operational bottlenecks. 

Your team should assign ownership for each alert, follow structured playbooks, such as re-scanning, re-booking, or escalating to carriers. They can also conduct weekly post-mortems by trade lane. This process ensures that recurring problems are addressed systematically and improvements are sustained.

Customer Communication & Experience (CX)

AI enhances customer experience by generating daily summaries of delivery performance and sending proactive status updates that reduce WISMO (Where Is My Order) inquiries. To complement this, you should provide self-serve tracking links, notify customers when ETAs shift, and monitor WISMO and CSAT scores by lane. Providing regular updates on your messaging based on these insights helps build trust and keeps customers informed throughout the delivery journey.

Final Takeaways: Turning Delivery Benchmarks into Competitive Advantage

In conclusion, our review of the Americas e-commerce shipping benchmarks Q2 2025 shows clear patterns– domestic lanes across the region continue to perform well, while cross-border routes reveal more complexity. Transit times, first-attempt delivery success, and issue ratios vary widely by lane, with factors like scan quality, customs delays, and pickup adoption playing key roles. AI Decision Intelligence helps retailers and logistics teams move from reactive to proactive. The solution can help in spotting problems early, refining delivery promises, and improving customer experience in real time.

To win in AI Commerce, retailers must promise precisely, act fast on alerts, rebalance the carrier mix by lane, and offer the right delivery option where it lifts success. That means tuning SLAs by region, surfacing flexible options at checkout, and using AI Decision Intelligence to guide every delivery decision. Ready to see how Parcel Perform’s AI Decision Intelligence can transform your logistics operations? Book a demo today and take the next step toward smarter, faster, and more reliable e-commerce delivery.

Frequently Asked Questions 

What KPIs matter most? 

Key performance indicators like transit time, on-time delivery ratio, first-attempt delivery success, and issue ratio are essential for measuring logistics performance. Supporting metrics, such as carrier vs. recipient issue split, collection-point usage, and dwell-time ratios, provide deeper context for operational decisions.

Q1 - Why do domestic lanes usually beat cross-border? 

Domestic deliveries typically outperform cross-border ones because they involve fewer handovers. Also, there are no customs clearance, shorter linehaul distances, and denser delivery zones. All of this can help reduce complexity and delays.

Q2 - How can I improve first-attempt success? 

You can boost first-attempt delivery rates by validating addresses upfront, offering accurate estimated delivery times, and enabling flexible delivery windows. Also, you can nudge recipients toward pickup or drop-off (PUDO) options when appropriate.

Q3 - How does AI Decision Intelligence reduce WISMO? 

AI Decision Intelligence helps reduce “Where is my order?” (WISMO) inquiries by identifying delivery exceptions early and triggering proactive, personalized updates that keep recipients informed before they need to ask.

Q4 - Should I add a buffer to hit a higher on-time rate? 

Adding excessive buffer time may improve on-time metrics, but often hurts conversion rates. Instead, use adaptive, data-driven delivery promises that balance reliability with speed and customer expectations.

Q5 - How often should I recalibrate EDD? 

Estimated delivery dates (EDD) should be recalibrated at least weekly to stay accurate. For volatile cross-border lanes, daily updates are recommended to reflect changing conditions and maintain trust.