Late parcels,angry reviews
A tested dbt + DuckDB warehouse over 99k orders from Olist, a Brazilian marketplace. Seven messy raw tables become documented marts with 59 data tests on every push. Then one question: what drives bad reviews, and what should operations fix first?
DataBrazilian E-Commerce Public Dataset by Olist: about 99k orders, Sep 2016 to Oct 2018, seven CSVs. Partial months are left out of the charts.
Seven CSVs to one tested warehouse
Each dot is a record. Staging fans out into one view per source table. Duplicate reviews are dropped so each order keeps one. Every layer is tested before the dashboard reads it. Click a stage to read what happens there.
The cliff starts at day one
Share of 1–2 star reviews by when the parcel arrived compared with the promised date. Early or on time, it stays near one in ten. One to three days late, it triples. Eight days late, four in five reviews are bad.
Average score4.32 for parcels 10+ days early; 1.70 for parcels 8+ days late. Only 6.8% of the 96,478 delivered orders were late, yet they hold most of the angry reviews.
Delivery failures, not demand
Two periods drove most late deliveries. Order volume was flat to rising across both, so each dip in reviews lines up with a delivery spike, not a change in demand.
Top categorieshealth_beauty (R$1.23M) and watches_gifts (R$1.17M). Total lifetime value across customers: R$15.42M.
São Paulo speed is not national speed
Average days from purchase to delivery. São Paulo receives 42% of orders and gets them in under nine days. The North and Northeast wait two to three times as long.
SuggestionPad estimates for the North and Northeast. Early parcels earn the best reviews, so a longer, honest promise costs little.
75 checks, one honest warning
The latest dbt build: 74 passes and one warning. The warning is real: 247 orders (0.26%) have payments that don't match items plus freight within R$1, mostly voucher top-ups. The test warns on any mismatch and fails above 500.
unique + not_null on every primary key.NextOnly 3.1% of customers order again. The next model to add links repeat purchase to the first order's delivery experience.