First-Attempt Delivery Rate Calculator

Mature parcel networks run 92–97% in mixed territory; 90% or below usually indicates fixable process gaps (notification, address quality, unattended options) rather than hard geography; 98%+ is realistic for B2B-heavy or leave-safe-heavy mixes. The composition matters as much as the headline: signature-required and COD parcels structurally fail more, apartments fail more than houses, and a mix shift can move your rate with no operational change. Benchmark against your own trend and segment before celebrating or panicking — and price the gap with the per-point value rather than treating the rate as cosmetic.

Stack the components: the wasted stop (a full stop's cost — $5–15 for most operations), the re-attempt (another stop), the support contacts a failure spawns (a large minority of failures generate at least one, at several dollars each), and the tail outcomes — pickup-point diversion, return-to-sender with reverse freight, refunds and occasional chargebacks. Fully loaded, $8–20 per failure is common. Multiply by your monthly failure count and the annual number usually surprises: a 4,000-delivery operation at 92% is spending tens of thousands a year on attempts that produced nothing.

For consumer delivery, precise day-of communication: a narrow predicted window (ideally live-tracking) plus an easy redirect path ('not home? choose a safe place / neighbor / locker') sent before the attempt. Customer absence is the dominant failure cause, and it's mostly an information problem — people aren't home because they didn't know when to be. Operations adding credible windows and pre-attempt notifications routinely report several points of improvement, which the per-point value turns into concrete money. After that: unattended-delivery options with photo proof, then checkout address validation for the long tail of bad data.

Measure them separately — they answer different questions. First-attempt rate isolates how well order data, communication and routing set up a deliverable stop; overall completion rate (within N attempts) measures the recovery machinery. Blending them hides problems: an operation can post a respectable completion rate while burning money on a weak first-attempt rate plus heroic re-attempts. The cost structure also differs — every re-attempt is incremental spend, so the efficient frontier is a HIGH first-attempt rate with a SHORT recovery tail (divert to pickup points after one or two failures rather than chasing a third).