Last-mile performance
Drive last-mile performance
A framework to help retailers and logistics service providers view the last mile as a unified, measurable business discipline that directly affects revenue, cost, and risk.
What is last-mile performance?
Market context
Citations: Cascadia Capital, 2024; Bringg Survey Research, 2026
- 65%
- of shoppers say a positive delivery experience convinced them to buy again, even at a higher price
- 55%
- of shoppers will abandon a brand because of a negative delivery experience
- 53%
- of total shipping costs come from last-mile delivery
Why does last-mile performance need a shared framework?
The data behind customer experience
Revenue metrics tie directly to top-line business outcomes. When they underperform, the impact shows up in lost sales, lost customers, declining lifetime value, and weakened customer trust.
The data that measures efficiency
Cost metrics reflect the operational efficiency of last-mile delivery. When they underperform, margin weakens gradually and invisibly until the cumulative impact becomes a financial problem.
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The data that shows gaps
This category captures the vulnerabilities in the delivery operation that, when unmanaged, lead to service failures and financial loss. Its primary metric is cancellation rate, covered under revenue metrics. That overlap is intentional. A canceled order reads as lost demand or as network risk depending on the cause.
The Metrics That Matter
- Cancellation rate
- Customer rating
- On time in full
- Cart conversion
- Delivery cost
- Dispatcher cost
- Customer care cost
- Driver utilization
Retailers have spent years measuring delivery in fragments. Last-mile performance is what happens when they finally measure it as one system.
Guy Bloch, CEO, Bringg
Last-mile performance metrics
Last-mile performance revenue metrics
Revenue
Cancellation rate
The share of placed orders canceled before delivery, whether by the retailer, the carrier, or the customer. Unlike returns, it captures demand that was accepted but never fulfilled.
- How it’s measured: Canceled orders ÷ total orders placed, segmented by cause (carrier-driven vs. merchant-initiated).
- Why it matters: It shows whether a business can deliver on the demand it accepts. When it rises, acquisition spend is wasted and affected customers are less likely to reorder.
Revenue
Customer rating
The score shoppers give their delivery experience, separate from product quality or brand sentiment.
- How it’s measured: Average score per order, driver, region, or delivery window, usually on a 1-to-5 scale collected right after delivery.
- Why it matters: It’s a leading indicator of repeat purchases, surfacing dissatisfaction before it shows up as churn. When ratings fall, customers order less often, spend less per order, and are more likely to switch to a competitor.
Revenue
On time in full
Whether an order arrives by the promised date, complete and undamaged, scored as a single pass or fail.
- How it’s measured: On-time, in-full deliveries ÷ total deliveries attempted, often segmented by carrier, region, or delivery method.
- Why it matters: It’s the most direct evidence that a business kept the promise made at checkout. Missed OTIF drives up WISMO calls and refund and reship costs, and pulls down customer ratings.
Revenue
Cart Conversion
The share of shoppers who complete checkout after reaching the delivery-options step, where cost, speed, and available windows are shown.
- How it’s measured: Completed orders ÷ shoppers who reached the delivery-options stage, often compared across free, standard, and expedited options.
- Why it matters: Delivery cost and speed are among the top reasons shoppers abandon carts, so this is one of the last chances to save a sale. Weak conversion here often gets blamed on price or product when the delivery promise is the real cause.
Revenue
Cancellation rate
The share of placed orders canceled before delivery, whether by the retailer, the carrier, or the customer. Unlike returns, it captures demand that was accepted but never fulfilled.
- How it’s measured: Canceled orders ÷ total orders placed, segmented by cause (carrier-driven vs. merchant-initiated).
- Why it matters: It shows whether a business can deliver on the demand it accepts. When it rises, acquisition spend is wasted and affected customers are less likely to reorder.
Revenue
Customer rating
The score shoppers give their delivery experience, separate from product quality or brand sentiment.
- How it’s measured: Average score per order, driver, region, or delivery window, usually on a 1-to-5 scale collected right after delivery.
- Why it matters: It’s a leading indicator of repeat purchases, surfacing dissatisfaction before it shows up as churn. When ratings fall, customers order less often, spend less per order, and are more likely to switch to a competitor.
Revenue
On time in full
Whether an order arrives by the promised date, complete and undamaged, scored as a single pass or fail.
- How it’s measured: On-time, in-full deliveries ÷ total deliveries attempted, often segmented by carrier, region, or delivery method.
- Why it matters: It’s the most direct evidence that a business kept the promise made at checkout. Missed OTIF drives up WISMO calls and refund and reship costs, and pulls down customer ratings.
Revenue
Cart Conversion
The share of shoppers who complete checkout after reaching the delivery-options step, where cost, speed, and available windows are shown.
- How it’s measured: Completed orders ÷ shoppers who reached the delivery-options stage, often compared across free, standard, and expedited options.
- Why it matters: Delivery cost and speed are among the top reasons shoppers abandon carts, so this is one of the last chances to save a sale. Weak conversion here often gets blamed on price or product when the delivery promise is the real cause.
Revenue
Cancellation rate
The share of placed orders canceled before delivery, whether by the retailer, the carrier, or the customer. Unlike returns, it captures demand that was accepted but never fulfilled.
- How it’s measured: Canceled orders ÷ total orders placed, segmented by cause (carrier-driven vs. merchant-initiated).
- Why it matters: It shows whether a business can deliver on the demand it accepts. When it rises, acquisition spend is wasted and affected customers are less likely to reorder.
Revenue
Customer rating
The score shoppers give their delivery experience, separate from product quality or brand sentiment.
- How it’s measured: Average score per order, driver, region, or delivery window, usually on a 1-to-5 scale collected right after delivery.
- Why it matters: It’s a leading indicator of repeat purchases, surfacing dissatisfaction before it shows up as churn. When ratings fall, customers order less often, spend less per order, and are more likely to switch to a competitor.
Revenue
On time in full
Whether an order arrives by the promised date, complete and undamaged, scored as a single pass or fail.
- How it’s measured: On-time, in-full deliveries ÷ total deliveries attempted, often segmented by carrier, region, or delivery method.
- Why it matters: It’s the most direct evidence that a business kept the promise made at checkout. Missed OTIF drives up WISMO calls and refund and reship costs, and pulls down customer ratings.
Revenue
Cart Conversion
The share of shoppers who complete checkout after reaching the delivery-options step, where cost, speed, and available windows are shown.
- How it’s measured: Completed orders ÷ shoppers who reached the delivery-options stage, often compared across free, standard, and expedited options.
- Why it matters: Delivery cost and speed are among the top reasons shoppers abandon carts, so this is one of the last chances to save a sale. Weak conversion here often gets blamed on price or product when the delivery promise is the real cause.
Last-mile performance cost metrics
Cost
Delivery cost
The direct cost of getting an order from dispatch to the customer’s door, driven mainly by distance and driver time per stop.
- How it’s measured: Total delivery expense (fuel, labor, vehicle) ÷ deliveries or stops, often segmented by route density, region, and delivery type.
- Why it matters: At more than half of total shipping cost, it’s the line item that ties last-mile execution most directly to margin. When it rises, retailers either absorb the loss or pass it on as higher shipping fees, which hurts cart conversion.
Cost
Dispatcher cost
The labor cost of planning, assigning, and adjusting routes and driver schedules, including manual fixes when plans change.
- How it’s measured: Planning labor hours or cost ÷ routes or orders dispatched, often tracked alongside time-to-action on delays, cancellations, and reroutes.
- Why it matters: It shows how much manual effort the network needs to run. High dispatcher cost limits how much volume a business can scale without adding headcount, and slow replanning ripples into missed OTIF and driver idle time.
Cost
Customer care cost
The cost of handling post-purchase delivery issues, mainly WISMO calls and exceptions like delays, damage, or missed deliveries.
- How it’s measured: Support labor cost ÷ delivery volume, often tracked alongside WISMO calls as a share of orders and time-to-resolution, segmented by cause.
- Why it matters: It’s a direct signal of visibility or reliability gaps elsewhere in the network. When it rises, upstream failures are landing on support teams instead of being prevented, which inflates cost-to-serve on every order.
Cost
Driver utilization
The share of a driver’s paid shift spent on active delivery work rather than idle time, waiting, or inefficient routing.
- How it’s measured: Active delivery time ÷ total paid shift time, often broken into idle, drive, and stop time per driver, route, or fleet.
- Why it matters: Labor is typically the largest last-mile expense, so utilization is one of the biggest levers on delivery cost. Low utilization means paying for capacity that produces nothing, which raises cost per delivery even on well-planned routes.
Cost
Delivery cost
The direct cost of getting an order from dispatch to the customer’s door, driven mainly by distance and driver time per stop.
- How it’s measured: Total delivery expense (fuel, labor, vehicle) ÷ deliveries or stops, often segmented by route density, region, and delivery type.
- Why it matters: At more than half of total shipping cost, it’s the line item that ties last-mile execution most directly to margin. When it rises, retailers either absorb the loss or pass it on as higher shipping fees, which hurts cart conversion.
Cost
Dispatcher cost
The labor cost of planning, assigning, and adjusting routes and driver schedules, including manual fixes when plans change.
- How it’s measured: Planning labor hours or cost ÷ routes or orders dispatched, often tracked alongside time-to-action on delays, cancellations, and reroutes.
- Why it matters: It shows how much manual effort the network needs to run. High dispatcher cost limits how much volume a business can scale without adding headcount, and slow replanning ripples into missed OTIF and driver idle time.
Cost
Customer care cost
The cost of handling post-purchase delivery issues, mainly WISMO calls and exceptions like delays, damage, or missed deliveries.
- How it’s measured: Support labor cost ÷ delivery volume, often tracked alongside WISMO calls as a share of orders and time-to-resolution, segmented by cause.
- Why it matters: It’s a direct signal of visibility or reliability gaps elsewhere in the network. When it rises, upstream failures are landing on support teams instead of being prevented, which inflates cost-to-serve on every order.
Cost
Driver utilization
The share of a driver’s paid shift spent on active delivery work rather than idle time, waiting, or inefficient routing.
- How it’s measured: Active delivery time ÷ total paid shift time, often broken into idle, drive, and stop time per driver, route, or fleet.
- Why it matters: Labor is typically the largest last-mile expense, so utilization is one of the biggest levers on delivery cost. Low utilization means paying for capacity that produces nothing, which raises cost per delivery even on well-planned routes.
Cost
Delivery cost
The direct cost of getting an order from dispatch to the customer’s door, driven mainly by distance and driver time per stop.
- How it’s measured: Total delivery expense (fuel, labor, vehicle) ÷ deliveries or stops, often segmented by route density, region, and delivery type.
- Why it matters: At more than half of total shipping cost, it’s the line item that ties last-mile execution most directly to margin. When it rises, retailers either absorb the loss or pass it on as higher shipping fees, which hurts cart conversion.
Cost
Dispatcher cost
The labor cost of planning, assigning, and adjusting routes and driver schedules, including manual fixes when plans change.
- How it’s measured: Planning labor hours or cost ÷ routes or orders dispatched, often tracked alongside time-to-action on delays, cancellations, and reroutes.
- Why it matters: It shows how much manual effort the network needs to run. High dispatcher cost limits how much volume a business can scale without adding headcount, and slow replanning ripples into missed OTIF and driver idle time.
Cost
Customer care cost
The cost of handling post-purchase delivery issues, mainly WISMO calls and exceptions like delays, damage, or missed deliveries.
- How it’s measured: Support labor cost ÷ delivery volume, often tracked alongside WISMO calls as a share of orders and time-to-resolution, segmented by cause.
- Why it matters: It’s a direct signal of visibility or reliability gaps elsewhere in the network. When it rises, upstream failures are landing on support teams instead of being prevented, which inflates cost-to-serve on every order.
Cost
Driver utilization
The share of a driver’s paid shift spent on active delivery work rather than idle time, waiting, or inefficient routing.
- How it’s measured: Active delivery time ÷ total paid shift time, often broken into idle, drive, and stop time per driver, route, or fleet.
- Why it matters: Labor is typically the largest last-mile expense, so utilization is one of the biggest levers on delivery cost. Low utilization means paying for capacity that produces nothing, which raises cost per delivery even on well-planned routes.
Last-mile performance risk metrics
Risk
Cancellation rate
The share of orders canceled because the delivery network couldn’t cover them, due to carrier coverage gaps or capacity shortfalls rather than pricing or inventory issues.
- How it’s measured: Canceled orders ÷ total orders, filtered to carrier- and capacity-driven causes. Retailers and LSPs often watch it most closely heading into peak season.
- Why it matters: It shows whether the network holds up under real demand. When it rises, the network is most fragile exactly when volume peaks (holidays, promotions, demand spikes), forcing costly last-minute capacity fixes or public delivery failures.
Risk
Cancellation rate
The share of orders canceled because the delivery network couldn’t cover them, due to carrier coverage gaps or capacity shortfalls rather than pricing or inventory issues.
- How it’s measured: Canceled orders ÷ total orders, filtered to carrier- and capacity-driven causes. Retailers and LSPs often watch it most closely heading into peak season.
- Why it matters: It shows whether the network holds up under real demand. When it rises, the network is most fragile exactly when volume peaks (holidays, promotions, demand spikes), forcing costly last-minute capacity fixes or public delivery failures.
Risk
Cancellation rate
The share of orders canceled because the delivery network couldn’t cover them, due to carrier coverage gaps or capacity shortfalls rather than pricing or inventory issues.
- How it’s measured: Canceled orders ÷ total orders, filtered to carrier- and capacity-driven causes. Retailers and LSPs often watch it most closely heading into peak season.
- Why it matters: It shows whether the network holds up under real demand. When it rises, the network is most fragile exactly when volume peaks (holidays, promotions, demand spikes), forcing costly last-minute capacity fixes or public delivery failures.
How last-mile performance metrics interconnect
They work together
The 8 last-mile performance indicators do not operate in isolation. They form a system of interdependencies where improvement in one metric often produces gains in others, and degradation in one creates compounding problems across the framework.
Revenue and cost connections
- OTIF improvements drive higher customer ratings
- Higher ratings lead to more repeat purchases and lower cancellation rates
- Fewer missed windows mean fewer re-deliveries, less driver idle time, and lower WISMO volume
- Better driver utilization improves OTIF, and better dispatcher efficiency lifts both
Cost metrics compound
- Greater dispatcher efficiency improves driver utilization
- Faster created-to-assign times mean fewer idle drivers and more productive delivery time
- Better route optimization raises drops per hour and lowers delivery cost per order
- Late assignments cause rushed routes, missed windows, WISMO calls, and increased customer care cost
Risk as an amplifier
- Cancellation rate's risk dimension acts as a threat multiplier
- A carrier coverage failure degrades OTIF across routes and spikes WISMO volume
- It lowers ratings and inflates cost as the business scrambles to recover
- Carrier diversification, predictive exceptions, and real-time capacity monitoring cut volatility across metrics
Cart conversion feedback loop
- Cart conversion happens at checkout but runs on trust built beforehand
- A strong OTIF track record supports tighter delivery promises
- High customer ratings build the confidence that drives conversion
- An aggressive promise the operation can't keep damages trust as fast as it captures the order
Silent retention leakage
- Delivery failures often surface silently as churn and lower customer lifetime value
- Customers rarely complain, so this gets misattributed to price, product, or competition
- That misattribution can push a business toward more acquisition spend or discounting to fix the "problem"
- Meanwhile, the real cause sits unaddressed in post-purchase execution, so the leak continues
They work together
The 8 last-mile performance indicators do not operate in isolation. They form a system of interdependencies where improvement in one metric often produces gains in others, and degradation in one creates compounding problems across the framework.
Revenue and cost connections
- OTIF improvements drive higher customer ratings
- Higher ratings lead to more repeat purchases and lower cancellation rates
- Fewer missed windows mean fewer re-deliveries, less driver idle time, and lower WISMO volume
- Better driver utilization improves OTIF, and better dispatcher efficiency lifts both
Cost metrics compound
- Greater dispatcher efficiency improves driver utilization
- Faster created-to-assign times mean fewer idle drivers and more productive delivery time
- Better route optimization raises drops per hour and lowers delivery cost per order
- Late assignments cause rushed routes, missed windows, WISMO calls, and increased customer care cost
Risk as an amplifier
- Cancellation rate's risk dimension acts as a threat multiplier
- A carrier coverage failure degrades OTIF across routes and spikes WISMO volume
- It lowers ratings and inflates cost as the business scrambles to recover
- Carrier diversification, predictive exceptions, and real-time capacity monitoring cut volatility across metrics
Cart conversion feedback loop
- Cart conversion happens at checkout but runs on trust built beforehand
- A strong OTIF track record supports tighter delivery promises
- High customer ratings build the confidence that drives conversion
- An aggressive promise the operation can't keep damages trust as fast as it captures the order
Silent retention leakage
- Delivery failures often surface silently as churn and lower customer lifetime value
- Customers rarely complain, so this gets misattributed to price, product, or competition
- That misattribution can push a business toward more acquisition spend or discounting to fix the "problem"
- Meanwhile, the real cause sits unaddressed in post-purchase execution, so the leak continues
They work together
The 8 last-mile performance indicators do not operate in isolation. They form a system of interdependencies where improvement in one metric often produces gains in others, and degradation in one creates compounding problems across the framework.
Revenue and cost connections
- OTIF improvements drive higher customer ratings
- Higher ratings lead to more repeat purchases and lower cancellation rates
- Fewer missed windows mean fewer re-deliveries, less driver idle time, and lower WISMO volume
- Better driver utilization improves OTIF, and better dispatcher efficiency lifts both
Cost metrics compound
- Greater dispatcher efficiency improves driver utilization
- Faster created-to-assign times mean fewer idle drivers and more productive delivery time
- Better route optimization raises drops per hour and lowers delivery cost per order
- Late assignments cause rushed routes, missed windows, WISMO calls, and increased customer care cost
Risk as an amplifier
- Cancellation rate's risk dimension acts as a threat multiplier
- A carrier coverage failure degrades OTIF across routes and spikes WISMO volume
- It lowers ratings and inflates cost as the business scrambles to recover
- Carrier diversification, predictive exceptions, and real-time capacity monitoring cut volatility across metrics
Cart conversion feedback loop
- Cart conversion happens at checkout but runs on trust built beforehand
- A strong OTIF track record supports tighter delivery promises
- High customer ratings build the confidence that drives conversion
- An aggressive promise the operation can't keep damages trust as fast as it captures the order
Silent retention leakage
- Delivery failures often surface silently as churn and lower customer lifetime value
- Customers rarely complain, so this gets misattributed to price, product, or competition
- That misattribution can push a business toward more acquisition spend or discounting to fix the "problem"
- Meanwhile, the real cause sits unaddressed in post-purchase execution, so the leak continues
Every business already has this data somewhere. LMP just organizes it so the causal relationships finally become visible.
Guy Bloch, CEO, Bringg
Putting LMP insights to action
Start by establishing a baseline across all 8 metrics. Most organizations find gaps in their measurement, not just their performance. Common examples are tracking OTIF without segmenting by delivery type, or measuring delivery cost in aggregate without isolating whether distance, driver time, or route density is driving it up.
