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Documentation Index

Fetch the complete documentation index at: https://docs.ocular.dev/llms.txt

Use this file to discover all available pages before exploring further.

All analyses on this page use the Fulfilment Data Model in Chart Builder and require the Clickpost connector to be live.
For each trigger below: what happened, where to go, how to read it, the decision you’re making.

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Which courier partner is costing us the most in failed deliveries?

Trigger: RTO rates climbing or delivery complaints rising. You need to know which courier — to renegotiate, reallocate, or escalate. Chart Builder: Fulfilment · Measures: rto_rate, delivery_rate, tat_breach_rate, avg_days_to_deliver · Dimension: courier_partner · Table sorted by rto_rate desc. A courier with high RTO and high TAT breach simultaneously → highest-risk partner. Every failure is an order lost plus reverse logistics cost. Add financial context: avg_shipment_cost alongside. Expensive and unreliable → strong candidate for reduced allocation. Decision: Reduce allocation, renegotiate terms, or escalate for performance review?

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Which cities or pincodes cause the most delivery failures?

Trigger: Overall RTO is high — is it concentrated in specific geographies (courier coverage issue) or spread evenly (payment method or product quality issue)? Chart Builder: Fulfilment · Measure: rto_rate · Dimension: drop_city · Breakdown: reason_for_first_failed_delivery · Pivot. The city × failure-reason matrix tells you whether failures are addressable (Customer Unavailable, Wrong Address — fixable with address validation, retry logic) or structural (courier doesn’t service the area — fixable only by changing allocation). Pincode granularity: Filter to drop_pincode for the highest-RTO cities. Specific pincodes often drive disproportionate failure shares. Decision: Address validation, switch courier for specific pincodes, or flag high-risk geos for COD?

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Are we being overbilled by courier partners?

Trigger: Logistics costs higher than expected, or WMS-declared vs. courier-invoiced weights are off. Quantify the gap and find responsible partners and zones. Chart Builder: Fulfilment · Measures: cost_discrepancy_rate, avg_weight_discrepancy, avg_shipment_cost · Dimension: courier_partner · Breakdown: zone · Table.
  • cost_discrepancy_rate — % shipments with billing mismatch
  • avg_weight_discrepancy — gap between WMS-declared and courier-billed weight
Couriers with high discrepancy rates in Metro and Zone A (where volumetric weight billing kicks in differently) → biggest source of unbilled cost. Decision: Which courier-zone combinations to flag for billing disputes, and do I need to recalibrate WMS weight declarations?

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How does COD delivery performance compare to prepaid?

Trigger: Considering tightening COD availability (specific pincodes, order values). Quantify the RTO penalty of COD vs. prepaid, broken down by courier. Chart Builder: Fulfilment · Measures: delivery_rate, rto_rate · Dimension: payment_method · Breakdown: courier_partner · Grouped Bar. COD has higher RTO by nature — buyers haven’t paid upfront. Interesting question: is the COD penalty courier-specific? If one courier has a dramatically higher COD RTO for the same zones, they’re not following up on failed COD deliveries. Decision: Restrict COD by pincode or order threshold, and stop assigning COD to specific couriers?

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What are the most common return and exchange reasons?

Trigger: High return volumes — is it sizing, quality, or misleading PDPs? The answer decides whether to fix the product, the listing, or fulfilment. Chart Builder: Fulfilment · Measure: returned_shipments · Dimension: return_reason · Bar sorted desc. Cross-reference with: Sales · Measure: percentage_orders_returned · Dimension: product_name, filtered to the high-return-reason categories. This connects the logistics reason (Clickpost) with the product dimension (Sales) — so you can see whether “Size issue” or “Not as described” concentrates in specific SKUs. Decision: Product issue (fix sizing, quality), listing issue (update PDP, images, size guide), or fulfilment issue (wrong items, packaging damage)?

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