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Time to ship

Shows order fulfillment time from order creation to fulfillment, with median, 75th, and 95th percentile callouts.

Authored by Intempt Technologies

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  1. 1

    Measure how fast orders ship

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About this recipe

When to use it

An average fulfillment time hides your worst-case tail. This histograms actual per-order fulfillment time with median, p75, and p95 called out, so slow outliers show up instead of getting averaged away.

What it delivers

Builds a histogram of per-order fulfillment time with median, 75th-percentile, and 95th-percentile callouts, giving real operational benchmarks instead of a single averaged figure.

How you prompt this

Describe the outcome in your own words and Blu Agent maps it to this recipe, or run it by name. It drafts a plan first and nothing runs until you approve it.

Tell Blu Agent what you want

“Shows order fulfillment time from order creation to fulfillment, with median, 75th, and 95th percentile callouts.”

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Inputs & outputs

What the recipe needs before it runs, and what it leaves in your workspace.

Inputs

  1. Nothing declared beyond an Intempt workspace. Blu asks for anything else it needs as it goes.

Outputs

    How the recipe runs

    Blu follows the steps in order and shows you each one before anything goes live.

    1. 01Measure how fast orders shipCreate an Insights report called "Time-to-Ship Distribution". Series A: Distribution histogram of fulfillment-time per order: computed by Lovable as (Order fulfilled.Created date − Placed order.Created date) for each fulfilled order, joined on order_id Buckets for Series A: 0 (24h / 24) 48h / 48 (72h / 3) 5 days / 5 (7 days / 7) 14 days / 14+ days Series B: Cumulative percentage: what % of orders ship within X time Time range: Last 30 days of Order fulfilled events (use the fulfillment date for cohorting, since orders fulfilled in the period may have been created before) Breakdown: By "source" property on Order fulfilled (warehouse, fulfillment center, or 3PL: varies by integration) OR by Users.country for geographic distribution analysis Compare: Previous period (prior 30 days) Chart type: Histogram chart with Series A as the bar distribution, Series B as a cumulative line overlay; secondary callouts for median, p75, p95 fulfillment times Annotations: - Add benchmarks: top-quartile DTC ships within 24h (Amazon-trained customer expectations); 24: 48h is industry median; >72h to first ship is competitively weak. - Flag if the share shipping within 24h dropped >10 percentage points vs. previous period (operational regression). - Flag the long tail: what % of orders take >7 days to ship? Anything above 5% is a fulfillment-process problem and a customer-experience issue (these customers are likely to complain or refund). - Highlight the median and p75 times as headline numbers: the median is the typical experience, p75 is the experience customers complain about, p95 is the experience that drives bad reviews. - Surface any source/warehouse with materially worse times than others: single facility issues are easier to fix than systemic ones. Use case: post-purchase customer experience is increasingly a competitive lever. Brands that ship fast retain better. This recipe makes the actual time-to-ship distribution visible (most ops dashboards only show "average ship time" which obscures the long tail). Taxonomy notes: - Placed order.Created date and Order fulfilled.Created date are both real datetime properties; the join is on order_id. - Order fulfilled.source is a real property (warehouse / 3PL identifier; varies by integration). - This recipe excludes orders where fulfillment hasn't yet occurred (no Order fulfilled event). For an "in-flight" backlog view, pair this recipe with order-status-flow.

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