Queries · q023 · Chief Financial Officer · week 1, night 4
“Which specific non-Apparel merchant(s) caused the refund-rate spike in 2025-Q2/Q3?”
Fictional people at a fictional company, each played by a language-model agent. Who they are and what they are told
The manager, at the start of week 1
Subject: Finding my bearings – first set of questions for the week
Hi Kofi,
Good to be working with you. I'm still building my mental map of the business, so I'd rather ask a few broad questions well than a lot of narrow ones badly. Given the slot budget, here's what I'd prioritize this week, roughly in order:
For this week, let's focus on #1 and #2 — those are the two I most need before I can speak credibly about 2025 and the 2026 budget. If there's room, #3 would be next; #4 and #5 can wait for a follow-up week if slots are tight.
Let me know if any of these need me to narrow scope further before you brief the data engineers.
Thanks, Tobias
The analyst · week 1, night 4, request 2 of 3
Report 1 confirms the fix: the corrected monthly series now ties exactly to the independently-verified 2025 annual totals (€3,972,987.99 gross / €93,583.20 fee / 2.4% blended fee rate), and payout counts roughly doubled vs. the original buggy report — consistent with it having silently dropped close to half of all payouts for a reason we never fully root-caused, but which is now moot since the corrected figures cross-foot cleanly. #1 is now safe to put in front of Tobias, with the one caveat I'll carry into the memo: nothing in this warehouse captures Tidewick's own platform-plan billing of merchants (the plans/subscriptions/invoices tables here model each merchant's billing of their customers, not Tidewick's billing of the merchant) — so I can only report the processing-fee half of the revenue split, not the plan-fee half.
On refunds, I did the arithmetic behind Report 2 and 3 by hand: subtracting Apparel's numbers from the company totals shows the non-Apparel refund rate was stable at ~2-3% through 2024, but spiked to 4.9% in 2025-Q2 and 9.1% in 2025-Q3 before dropping back to 4.2% in Q4 — a 3-4x jump that Apparel's own flat/improving trend doesn't explain. Apparel itself looks structural (19-26% every quarter, actually lowest in the latest quarter), so that part of #3 is answered and not worsening. But this non-Apparel spike is new information worth chasing on this last night before the memo, since it could be a specific merchant issue (e.g. a product recall or quality problem) rather than normal seasonal variation. I'm spending two slots to localize it (by vertical, then by merchant) and a third to cross-check the payments-based refund figures against the independent order_returns table, given how costly the earlier monthly-revenue bug was — I don't want to hand Tobias a refund narrative built on a single, unverified source.
The engineer · 2 dry runs on the empty schema, then the submission
WITH fx AS ( SELECT quote_code, as_of, rate FROM exchange_rates WHERE base_code = 'EUR' ), base AS ( SELECT p.tenant_id, p.currency_code, p.amount, p.amount_refunded, CAST(p.captured_at AS date) AS captured_date, EXTRACT(QUARTER FROM p.captured_at)::int AS q FROM payments p JOIN tenants t ON t.id = p.tenant_id WHERE (t.industry IS DISTINCT FROM 'Apparel & Footwear') AND p.status IN ('captured', 'refunded', 'partially_refunded') AND p.captured_at >= TIMESTAMP '2025-01-01' AND p.captured_at < TIMESTAMP '2026-01-01' ), converted AS ( SELECT b.tenant_id, b.q, CASE WHEN b.currency_code = 'EUR' THEN b.amount ELSE b.amount / fx.rate END AS amount_eur, CASE WHEN b.currency_code = 'EUR' THEN b.amount_refunded ELSE b.amount_refunded / fx.rate END AS refunded_eur FROM base b LEFT JOIN fx ON fx.quote_code = b.currency_code AND fx.as_of = b.captured_date ), tenant_quarter AS ( SELECT tenant_id, q, SUM(amount_eur) AS gross_eur, SUM(refunded_eur) AS refunded_eur, COUNT(*) AS cnt FROM converted GROUP BY tenant_id, q ), tenant_total AS ( SELECT tenant_id, SUM(gross_eur) AS gross_eur_fy, SUM(refunded_eur) AS refunded_eur_fy, SUM(cnt) AS cnt_fy FROM tenant_quarter GROUP BY tenant_id ), qualified AS ( SELECT tenant_id FROM tenant_total WHERE cnt_fy >= 20 ), pivot AS ( SELECT tt.tenant_id, tt.gross_eur_fy, tt.refunded_eur_fy, MAX(CASE WHEN tq.q = 1 THEN tq.gross_eur END) AS q1_gross, MAX(CASE WHEN tq.q = 1 THEN tq.refunded_eur END) AS q1_ref, MAX(CASE WHEN tq.q = 2 THEN tq.gross_eur END) AS q2_gross, MAX(CASE WHEN tq.q = 2 THEN tq.refunded_eur END) AS q2_ref, MAX(CASE WHEN tq.q = 3 THEN tq.gross_eur END) AS q3_gross, MAX(CASE WHEN tq.q = 3 THEN tq.refunded_eur END) AS q3_ref, MAX(CASE WHEN tq.q = 4 THEN tq.gross_eur END) AS q4_gross, MAX(CASE WHEN tq.q = 4 THEN tq.refunded_eur END) AS q4_ref FROM tenant_total tt JOIN tenant_quarter tq ON tq.tenant_id = tt.tenant_id WHERE tt.tenant_id IN (SELECT tenant_id FROM qualified) GROUP BY tt.tenant_id, tt.gross_eur_fy, tt.refunded_eur_fy ) SELECT t.name AS merchant_name, t.industry AS vertical, ROUND(p.gross_eur_fy, 2) AS gross_captured_eur_fy2025, ROUND(100.0 * p.q1_ref / NULLIF(p.q1_gross, 0), 2) AS refund_rate_q1_pct, ROUND(100.0 * p.q2_ref / NULLIF(p.q2_gross, 0), 2) AS refund_rate_q2_pct, ROUND(100.0 * p.q3_ref / NULLIF(p.q3_gross, 0), 2) AS refund_rate_q3_pct, ROUND(100.0 * p.q4_ref / NULLIF(p.q4_gross, 0), 2) AS refund_rate_q4_pct, ROUND(100.0 * p.refunded_eur_fy / NULLIF(p.gross_eur_fy, 0), 2) AS refund_rate_fy2025_pct FROM pivot p JOIN tenants t ON t.id = p.tenant_id ORDER BY refund_rate_q3_pct DESC NULLS LAST, merchant_name ASC LIMIT 30
WITH fx AS ( SELECT quote_code, as_of, rate FROM exchange_rates WHERE base_code = 'EUR'),base AS ( SELECT p.tenant_id, p.currency_code, p.amount, p.amount_refunded, CAST(p.captured_at AS date) AS captured_date, EXTRACT(QUARTER FROM p.captured_at)::int AS q FROM payments p JOIN tenants t ON t.id = p.tenant_id WHERE (t.industry IS DISTINCT FROM 'Apparel & Footwear') AND p.status IN ('captured', 'refunded', 'partially_refunded') AND p.captured_at >= TIMESTAMP '2025-01-01' AND p.captured_at < TIMESTAMP '2026-01-01'),converted AS ( SELECT b.tenant_id, b.q, CASE WHEN b.currency_code = 'EUR' THEN b.amount ELSE b.amount / fx.rate END AS amount_eur, CASE WHEN b.currency_code = 'EUR' THEN b.amount_refunded ELSE b.amount_refunded / fx.rate END AS refunded_eur FROM base b LEFT JOIN fx ON fx.quote_code = b.currency_code AND fx.as_of = b.captured_date),tenant_quarter AS ( SELECT tenant_id, q, SUM(amount_eur) AS gross_eur, SUM(refunded_eur) AS refunded_eur, COUNT(*) AS cnt FROM converted GROUP BY tenant_id, q),tenant_total AS ( SELECT tenant_id, SUM(gross_eur) AS gross_eur_fy, SUM(refunded_eur) AS refunded_eur_fy, SUM(cnt) AS cnt_fy FROM tenant_quarter GROUP BY tenant_id),qualified AS ( SELECT tenant_id FROM tenant_total WHERE cnt_fy >= 20),pivot AS (pivoted AS ( SELECT tt.tenant_id, tt.gross_eur_fy, tt.refunded_eur_fy, MAX(CASE WHEN tq.q = 1 THEN tq.gross_eur END) AS q1_gross, MAX(CASE WHEN tq.q = 1 THEN tq.refunded_eur END) AS q1_ref, MAX(CASE WHEN tq.q = 2 THEN tq.gross_eur END) AS q2_gross, MAX(CASE WHEN tq.q = 2 THEN tq.refunded_eur END) AS q2_ref, MAX(CASE WHEN tq.q = 3 THEN tq.gross_eur END) AS q3_gross, MAX(CASE WHEN tq.q = 3 THEN tq.refunded_eur END) AS q3_ref, MAX(CASE WHEN tq.q = 4 THEN tq.gross_eur END) AS q4_gross, MAX(CASE WHEN tq.q = 4 THEN tq.refunded_eur END) AS q4_ref FROM tenant_total tt JOIN tenant_quarter tq ON tq.tenant_id = tt.tenant_id WHERE tt.tenant_id IN (SELECT tenant_id FROM qualified) GROUP BY tt.tenant_id, tt.gross_eur_fy, tt.refunded_eur_fy)SELECT t.name AS merchant_name, t.industry AS vertical, ROUND(p.gross_eur_fy, 2) AS gross_captured_eur_fy2025, ROUND(100.0 * p.q1_ref / NULLIF(p.q1_gross, 0), 2) AS refund_rate_q1_pct, ROUND(100.0 * p.q2_ref / NULLIF(p.q2_gross, 0), 2) AS refund_rate_q2_pct, ROUND(100.0 * p.q3_ref / NULLIF(p.q3_gross, 0), 2) AS refund_rate_q3_pct, ROUND(100.0 * p.q4_ref / NULLIF(p.q4_gross, 0), 2) AS refund_rate_q4_pct, ROUND(100.0 * p.refunded_eur_fy / NULLIF(p.gross_eur_fy, 0), 2) AS refund_rate_fy2025_pctFROM pivot pFROM pivoted pJOIN tenants t ON t.id = p.tenant_idORDER BY refund_rate_q3_pct DESC NULLS LAST, merchant_name ASCLIMIT 30
“Query compiles correctly with the expected 8 columns. Submitting now.”
“Submitted. Summary of what the query does:
- Filters payments to 2025 captures with status in (captured, refunded, partially_refunded), joined to tenants, excluding industry = 'Apparel & Footwear'.
- Converts amount and amount_refunded to EUR per row using the day's exchange_rates (base EUR), matching on captured_at's date.
- Aggregates gross and refunded EUR per tenant per quarter, then totals for the year.
- Keeps only tenants with ≥20 qualifying payments in 2025.
- Pivots quarters into columns and computes refund-rate % (refunded/gross) for Q1–Q4 and FY2025.
- Orders by Q3 refund rate descending (tie-break by merchant name), returns top 30 rows, one row per merchant.
Note sent to the analyst: the excluded-tenant count from the ≥20-payment threshold isn't representable at this per-tenant grain (would need a separate single-row report), and quarters with zero gross for a tenant show a null rate rather than a divide-by-zero error.”
As Kofi Mensah saw it, from the small dataset the agents worked on
merchant_name | vertical | gross_captured_eur_fy2025 | refund_rate_q1_pct | refund_rate_q2_pct | refund_rate_q3_pct | refund_rate_q4_pct | refund_rate_fy2025_pct -----------------------+---------------------------+---------------------------+--------------------+--------------------+--------------------+--------------------+----------------------- Fell & Fjell | Sports & Outdoor | 36116.68 | 2.4 | 7.97 | 34.28 | 4.36 | 16.2 Trailmark | Sports & Outdoor | 7428.21 | NULL | 2.28 | 24.84 | 39.42 | 31.37 OfficeHub Nordic | Office Supplies (B2B) | 426010.27 | 0.0 | 6.59 | 20.98 | 0.0 | 6.96 Linden & Loom | Home & Living | 37516.18 | 5.88 | 14.69 | 16.4 | 6.84 | 9.44 Gratlinie Outdoor | Sports & Outdoor | 94789.94 | 11.77 | 6.02 | 14.48 | 17.01 | 12.51 Petalcourt Beauty | Beauty | 61911.92 | 2.53 | 2.34 | 12.83 | 7.0 | 6.52 Ampere & Co. | Consumer Electronics | 28882.99 | 2.06 | 0.85 | 12.42 | 1.33 | 2.65 Nordic Bloom Cosmetics | Beauty | 17564.54 | 11.96 | 0.0 | 12.19 | 8.67 | 7.94 Willow & Wren | Home & Living | 18796.06 | 18.55 | 2.7 | 11.2 | 12.23 | 12.78 Ridgeback Gear | Sports & Outdoor | 27032.69 | 13.81 | 4.64 | 10.42 | 23.61 | 13.41 Wiesgrund Wohnen | Home & Living | 37511.41 | 8.82 | 3.22 | 9.85 | 8.08 | 7.58 Saffron & Sage | Beauty | 9866.32 | 0.0 | 0.0 | 9.62 | 11.76 | 7.48 Polder Packaging | Industrial Supplies (B2B) | 90872.65 | 0.0 | 0.0 | 9.08 | 0.0 | 2.79 Juniper Apothecary | Beauty | 17551.04 | 4.71 | 5.69 | 8.85 | 1.82 | 4.75 Fern & Fable | Home & Living | 5535.53 | 0.0 | 0.0 | 8.59 | 7.32 | 5.6 Cinder Peak Sports Co. | Sports & Outdoor | 123713.44 | 13.07 | 16.06 | 7.57 | 16.02 | 13.51 Midland Safety Wear | Industrial Supplies (B2B) | 297398.75 | 0.0 | 0.02 | 7.3 | 4.14 | 3.78 Chocolaterie Mireille | Food & Coffee | 5122.68 | 0.0 | 0.0 | 6.5 | 0.65 | 2.16 Mirelle | Beauty | 4582.59 | 0.0 | 0.0 | 5.99 | 1.23 | 1.92 Spice Route Box | Food & Coffee | 26524.61 | 0.18 | 0.49 | 5.66 | 0.21 | 1.4 Ondine Botanicals | Beauty | 2193.24 | 0.0 | 0.0 | 5.41 | 30.38 | 8.94 Basecamp Nord | Sports & Outdoor | 9869.46 | 0.0 | 7.5 | 5.3 | 8.16 | 5.59 Velo Noord | Sports & Outdoor | 9780.02 | 14.31 | 31.83 | 5.16 | 8.48 | 11.39 The Balm Room | Beauty | 13879.18 | 6.22 | 2.06 | 4.55 | 6.44 | 5.28 Wohnglück | Home & Living | 21016.27 | 5.16 | 11.82 | 4.45 | 7.0 | 6.79 Kayak Corner | Sports & Outdoor | 39742.21 | 12.31 | 9.65 | 4.32 | 3.38 | 8.51 Fennel & Flint | Home & Living | 64363.83 | 7.67 | 10.76 | 4.29 | 3.96 | 5.84 Feather & Fin | Pet Supplies | 10162.91 | 1.1 | 0.0 | 3.9 | 8.7 | 4.09 Coastline Interiors | Home & Living | 20804.3 | 2.76 | 15.09 | 3.24 | 6.03 | 6.39 Honeycomb Larder | Food & Coffee | 31948.08 | 0.0 | 1.6 | 3.18 | 0.06 | 0.99 (30 rows)
The memo and the queries that followed; links found by title, so inferred
It builds on:
Changed only where the benchmark needs the same result on every system
WITH fx AS ( SELECT quote_code, as_of, rate FROM exchange_rates WHERE base_code = 'EUR'),base AS ( SELECT p.tenant_id, p.currency_code, p.amount, p.amount_refunded, p.tenant_id AS tenant_id, p.currency_code AS currency_code, p.amount AS amount, p.amount_refunded AS amount_refunded, CAST(p.captured_at AS date) AS captured_date, EXTRACT(QUARTER FROM p.captured_at)::int AS q CAST(EXTRACT(QUARTER FROM p.captured_at) AS int) AS q FROM payments p JOIN tenants t ON t.id = p.tenant_id WHERE (t.industry IS DISTINCT FROM 'Apparel & Footwear') AND p.status IN ('captured', 'refunded', 'partially_refunded') AND p.captured_at >= TIMESTAMP '2025-01-01' AND p.captured_at < TIMESTAMP '2026-01-01'),converted AS ( SELECT b.tenant_id, b.q, CASE WHEN b.currency_code = 'EUR' THEN b.amount ELSE b.amount / fx.rate END AS amount_eur, CASE WHEN b.currency_code = 'EUR' THEN b.amount_refunded ELSE b.amount_refunded / fx.rate END AS refunded_eur b.tenant_id AS tenant_id, b.q AS q, CASE WHEN b.currency_code = 'EUR' THEN b.amount ELSE CAST(b.amount / fx.rate AS NUMERIC(18,6)) END AS amount_eur, CASE WHEN b.currency_code = 'EUR' THEN b.amount_refunded ELSE CAST(b.amount_refunded / fx.rate AS NUMERIC(18,6)) END AS refunded_eur FROM base b LEFT JOIN fx ON fx.quote_code = b.currency_code AND fx.as_of = b.captured_date),tenant_quarter AS ( SELECT tenant_id, q, SUM(amount_eur) AS gross_eur, SUM(refunded_eur) AS refunded_eur, COUNT(*) AS cnt FROM converted GROUP BY tenant_id, q),tenant_total AS ( SELECT tenant_id, SUM(gross_eur) AS gross_eur_fy, SUM(refunded_eur) AS refunded_eur_fy, SUM(cnt) AS cnt_fy FROM tenant_quarter GROUP BY tenant_id),qualified AS ( SELECT tenant_id FROM tenant_total WHERE cnt_fy >= 20),pivoted AS ( SELECT tt.tenant_id, tt.gross_eur_fy, tt.refunded_eur_fy, tt.tenant_id AS tenant_id, tt.gross_eur_fy AS gross_eur_fy, tt.refunded_eur_fy AS refunded_eur_fy, MAX(CASE WHEN tq.q = 1 THEN tq.gross_eur END) AS q1_gross, MAX(CASE WHEN tq.q = 1 THEN tq.refunded_eur END) AS q1_ref, MAX(CASE WHEN tq.q = 2 THEN tq.gross_eur END) AS q2_gross, MAX(CASE WHEN tq.q = 2 THEN tq.refunded_eur END) AS q2_ref, MAX(CASE WHEN tq.q = 3 THEN tq.gross_eur END) AS q3_gross, MAX(CASE WHEN tq.q = 3 THEN tq.refunded_eur END) AS q3_ref, MAX(CASE WHEN tq.q = 4 THEN tq.gross_eur END) AS q4_gross, MAX(CASE WHEN tq.q = 4 THEN tq.refunded_eur END) AS q4_ref FROM tenant_total tt JOIN tenant_quarter tq ON tq.tenant_id = tt.tenant_id WHERE tt.tenant_id IN (SELECT tenant_id FROM qualified) GROUP BY tt.tenant_id, tt.gross_eur_fy, tt.refunded_eur_fy)SELECT t.name AS merchant_name, t.industry AS vertical, ROUND(p.gross_eur_fy, 2) AS gross_captured_eur_fy2025, ROUND(100.0 * p.q1_ref / NULLIF(p.q1_gross, 0), 2) AS refund_rate_q1_pct, ROUND(100.0 * p.q2_ref / NULLIF(p.q2_gross, 0), 2) AS refund_rate_q2_pct, ROUND(100.0 * p.q3_ref / NULLIF(p.q3_gross, 0), 2) AS refund_rate_q3_pct, ROUND(100.0 * p.q4_ref / NULLIF(p.q4_gross, 0), 2) AS refund_rate_q4_pct, ROUND(100.0 * p.refunded_eur_fy / NULLIF(p.gross_eur_fy, 0), 2) AS refund_rate_fy2025_pct p.gross_eur_fy AS gross_captured_eur_fy2025, 100.0 * p.q1_ref / NULLIF(p.q1_gross, 0) AS refund_rate_q1_pct, 100.0 * p.q2_ref / NULLIF(p.q2_gross, 0) AS refund_rate_q2_pct, 100.0 * p.q3_ref / NULLIF(p.q3_gross, 0) AS refund_rate_q3_pct, 100.0 * p.q4_ref / NULLIF(p.q4_gross, 0) AS refund_rate_q4_pct, 100.0 * p.refunded_eur_fy / NULLIF(p.gross_eur_fy, 0) AS refund_rate_fy2025_pctFROM pivoted pJOIN tenants t ON t.id = p.tenant_idORDER BY refund_rate_q3_pct DESC NULLS LAST, merchant_name ASCLIMIT 30ORDER BY refund_rate_q3_pct DESC NULLS LAST, merchant_name ASC NULLS LAST, t.id NULLS LAST{{fetch_first(30)}}
WITH fx AS ( SELECT quote_code, as_of, rate FROM exchange_rates WHERE base_code = 'EUR' ), base AS ( SELECT p.tenant_id AS tenant_id, p.currency_code AS currency_code, p.amount AS amount, p.amount_refunded AS amount_refunded, CAST(p.captured_at AS date) AS captured_date, CAST(EXTRACT(QUARTER FROM p.captured_at) AS int) AS q FROM payments p JOIN tenants t ON t.id = p.tenant_id WHERE (t.industry IS DISTINCT FROM 'Apparel & Footwear') AND p.status IN ('captured', 'refunded', 'partially_refunded') AND p.captured_at >= TIMESTAMP '2025-01-01' AND p.captured_at < TIMESTAMP '2026-01-01' ), converted AS ( SELECT b.tenant_id AS tenant_id, b.q AS q, CASE WHEN b.currency_code = 'EUR' THEN b.amount ELSE CAST(b.amount / fx.rate AS NUMERIC(18,6)) END AS amount_eur, CASE WHEN b.currency_code = 'EUR' THEN b.amount_refunded ELSE CAST(b.amount_refunded / fx.rate AS NUMERIC(18,6)) END AS refunded_eur FROM base b LEFT JOIN fx ON fx.quote_code = b.currency_code AND fx.as_of = b.captured_date ), tenant_quarter AS ( SELECT tenant_id, q, SUM(amount_eur) AS gross_eur, SUM(refunded_eur) AS refunded_eur, COUNT(*) AS cnt FROM converted GROUP BY tenant_id, q ), tenant_total AS ( SELECT tenant_id, SUM(gross_eur) AS gross_eur_fy, SUM(refunded_eur) AS refunded_eur_fy, SUM(cnt) AS cnt_fy FROM tenant_quarter GROUP BY tenant_id ), qualified AS ( SELECT tenant_id FROM tenant_total WHERE cnt_fy >= 20 ), pivoted AS ( SELECT tt.tenant_id AS tenant_id, tt.gross_eur_fy AS gross_eur_fy, tt.refunded_eur_fy AS refunded_eur_fy, MAX(CASE WHEN tq.q = 1 THEN tq.gross_eur END) AS q1_gross, MAX(CASE WHEN tq.q = 1 THEN tq.refunded_eur END) AS q1_ref, MAX(CASE WHEN tq.q = 2 THEN tq.gross_eur END) AS q2_gross, MAX(CASE WHEN tq.q = 2 THEN tq.refunded_eur END) AS q2_ref, MAX(CASE WHEN tq.q = 3 THEN tq.gross_eur END) AS q3_gross, MAX(CASE WHEN tq.q = 3 THEN tq.refunded_eur END) AS q3_ref, MAX(CASE WHEN tq.q = 4 THEN tq.gross_eur END) AS q4_gross, MAX(CASE WHEN tq.q = 4 THEN tq.refunded_eur END) AS q4_ref FROM tenant_total tt JOIN tenant_quarter tq ON tq.tenant_id = tt.tenant_id WHERE tt.tenant_id IN (SELECT tenant_id FROM qualified) GROUP BY tt.tenant_id, tt.gross_eur_fy, tt.refunded_eur_fy ) SELECT t.name AS merchant_name, t.industry AS vertical, p.gross_eur_fy AS gross_captured_eur_fy2025, 100.0 * p.q1_ref / NULLIF(p.q1_gross, 0) AS refund_rate_q1_pct, 100.0 * p.q2_ref / NULLIF(p.q2_gross, 0) AS refund_rate_q2_pct, 100.0 * p.q3_ref / NULLIF(p.q3_gross, 0) AS refund_rate_q3_pct, 100.0 * p.q4_ref / NULLIF(p.q4_gross, 0) AS refund_rate_q4_pct, 100.0 * p.refunded_eur_fy / NULLIF(p.gross_eur_fy, 0) AS refund_rate_fy2025_pct FROM pivoted p JOIN tenants t ON t.id = p.tenant_id ORDER BY refund_rate_q3_pct DESC NULLS LAST, merchant_name ASC NULLS LAST, t.id NULLS LAST FETCH FIRST 30 ROWS ONLY
WITH fx AS ( SELECT quote_code, as_of, rate FROM exchange_rates WHERE base_code = 'EUR' ), base AS ( SELECT p.tenant_id AS tenant_id, p.currency_code AS currency_code, p.amount AS amount, p.amount_refunded AS amount_refunded, CAST(p.captured_at AS date) AS captured_date, CAST(EXTRACT(QUARTER FROM p.captured_at) AS int) AS q FROM payments p JOIN tenants t ON t.id = p.tenant_id WHERE (t.industry IS DISTINCT FROM 'Apparel & Footwear') AND p.status IN ('captured', 'refunded', 'partially_refunded') AND p.captured_at >= TIMESTAMP '2025-01-01' AND p.captured_at < TIMESTAMP '2026-01-01' ), converted AS ( SELECT b.tenant_id AS tenant_id, b.q AS q, CASE WHEN b.currency_code = 'EUR' THEN b.amount ELSE CAST(b.amount / fx.rate AS NUMERIC(18,6)) END AS amount_eur, CASE WHEN b.currency_code = 'EUR' THEN b.amount_refunded ELSE CAST(b.amount_refunded / fx.rate AS NUMERIC(18,6)) END AS refunded_eur FROM base b LEFT JOIN fx ON fx.quote_code = b.currency_code AND fx.as_of = b.captured_date ), tenant_quarter AS ( SELECT tenant_id, q, SUM(amount_eur) AS gross_eur, SUM(refunded_eur) AS refunded_eur, COUNT(*) AS cnt FROM converted GROUP BY tenant_id, q ), tenant_total AS ( SELECT tenant_id, SUM(gross_eur) AS gross_eur_fy, SUM(refunded_eur) AS refunded_eur_fy, SUM(cnt) AS cnt_fy FROM tenant_quarter GROUP BY tenant_id ), qualified AS ( SELECT tenant_id FROM tenant_total WHERE cnt_fy >= 20 ), pivoted AS ( SELECT tt.tenant_id AS tenant_id, tt.gross_eur_fy AS gross_eur_fy, tt.refunded_eur_fy AS refunded_eur_fy, MAX(CASE WHEN tq.q = 1 THEN tq.gross_eur END) AS q1_gross, MAX(CASE WHEN tq.q = 1 THEN tq.refunded_eur END) AS q1_ref, MAX(CASE WHEN tq.q = 2 THEN tq.gross_eur END) AS q2_gross, MAX(CASE WHEN tq.q = 2 THEN tq.refunded_eur END) AS q2_ref, MAX(CASE WHEN tq.q = 3 THEN tq.gross_eur END) AS q3_gross, MAX(CASE WHEN tq.q = 3 THEN tq.refunded_eur END) AS q3_ref, MAX(CASE WHEN tq.q = 4 THEN tq.gross_eur END) AS q4_gross, MAX(CASE WHEN tq.q = 4 THEN tq.refunded_eur END) AS q4_ref FROM tenant_total tt JOIN tenant_quarter tq ON tq.tenant_id = tt.tenant_id WHERE tt.tenant_id IN (SELECT tenant_id FROM qualified) GROUP BY tt.tenant_id, tt.gross_eur_fy, tt.refunded_eur_fy ) SELECT t.name AS merchant_name, t.industry AS vertical, p.gross_eur_fy AS gross_captured_eur_fy2025, 100.0 * p.q1_ref / NULLIF(p.q1_gross, 0) AS refund_rate_q1_pct, 100.0 * p.q2_ref / NULLIF(p.q2_gross, 0) AS refund_rate_q2_pct, 100.0 * p.q3_ref / NULLIF(p.q3_gross, 0) AS refund_rate_q3_pct, 100.0 * p.q4_ref / NULLIF(p.q4_gross, 0) AS refund_rate_q4_pct, 100.0 * p.refunded_eur_fy / NULLIF(p.gross_eur_fy, 0) AS refund_rate_fy2025_pct FROM pivoted p JOIN tenants t ON t.id = p.tenant_id ORDER BY refund_rate_q3_pct DESC NULLS LAST, merchant_name ASC NULLS LAST, t.id NULLS LAST LIMIT 30
The agents' own records, as the role play wrote them; only the personal data of the person who ran it is redacted
Report request from Kofi Mensah (analyst for the Chief Financial Officer): Title: Merchant-Level Quarterly Refund Rate, 2025 (excluding Apparel & Footwear) Question: Which specific non-Apparel merchant(s) caused the refund-rate spike in 2025-Q2/Q3? Grain: one tenant (merchant), for 2025, with quarterly refund rates as columns Columns: - merchant_name - vertical - gross_captured_eur_fy2025 - refund_rate_q1_pct - refund_rate_q2_pct - refund_rate_q3_pct - refund_rate_q4_pct - refund_rate_fy2025_pct Details: Source: payments joined to tenants, excluding tenants.industry = 'Apparel & Footwear', filtered to status reflecting captured/refunded/partially_refunded with captured_at in calendar year 2025. Convert amount and amount_refunded to EUR via exchange_rates as in the vertical-quarter report. For each tenant, compute refund_rate_pct (amount_refunded_eur / gross_captured_eur * 100) separately for each of Q1-Q4 2025 and for the full year, pivoted into one row per tenant. Restrict to tenants with at least 20 qualifying payments in 2025 total, to avoid single-payment noise (note in the report how many tenants were excluded by this threshold). Order by refund_rate_q3_pct descending, tie-break merchant_name ascending; print the top 30 rows. Check your query with the warehouse's dry_run tool, then hand it in with submit.
dry_runWITH fx AS ( SELECT quote_code, as_of, rate FROM exchange_rates WHERE base_code = 'EUR' ), base AS ( SELECT p.tenant_id, p.currency_code, p.amount, p.amount_refunded, CAST(p.captured_at AS date) AS captured_date, EXTRACT(QUARTER FROM p.captured_at)::int AS q FROM payments p JOIN tenants t ON t.id = p.tenant_id WHERE (t.industry IS DISTINCT FROM 'Apparel & Footwear') AND p.status IN ('captured', 'refunded', 'partially_refunded') AND p.captured_at >= TIMESTAMP '2025-01-01' AND p.captured_at < TIMESTAMP '2026-01-01' ), converted AS ( SELECT b.tenant_id, b.q, CASE WHEN b.currency_code = 'EUR' THEN b.amount ELSE b.amount / fx.rate END AS amount_eur, CASE WHEN b.currency_code = 'EUR' THEN b.amount_refunded ELSE b.amount_refunded / fx.rate END AS refunded_eur FROM base b LEFT JOIN fx ON fx.quote_code = b.currency_code AND fx.as_of = b.captured_date ), tenant_quarter AS ( SELECT tenant_id, q, SUM(amount_eur) AS gross_eur, SUM(refunded_eur) AS refunded_eur, COUNT(*) AS cnt FROM converted GROUP BY tenant_id, q ), tenant_total AS ( SELECT tenant_id, SUM(gross_eur) AS gross_eur_fy, SUM(refunded_eur) AS refunded_eur_fy, SUM(cnt) AS cnt_fy FROM tenant_quarter GROUP BY tenant_id ), qualified AS ( SELECT tenant_id FROM tenant_total WHERE cnt_fy >= 20 ), pivot AS ( SELECT tt.tenant_id, tt.gross_eur_fy, tt.refunded_eur_fy, MAX(CASE WHEN tq.q = 1 THEN tq.gross_eur END) AS q1_gross, MAX(CASE WHEN tq.q = 1 THEN tq.refunded_eur END) AS q1_ref, MAX(CASE WHEN tq.q = 2 THEN tq.gross_eur END) AS q2_gross, MAX(CASE WHEN tq.q = 2 THEN tq.refunded_eur END) AS q2_ref, MAX(CASE WHEN tq.q = 3 THEN tq.gross_eur END) AS q3_gross, MAX(CASE WHEN tq.q = 3 THEN tq.refunded_eur END) AS q3_ref, MAX(CASE WHEN tq.q = 4 THEN tq.gross_eur END) AS q4_gross, MAX(CASE WHEN tq.q = 4 THEN tq.refunded_eur END) AS q4_ref FROM tenant_total tt JOIN tenant_quarter tq ON tq.tenant_id = tt.tenant_id WHERE tt.tenant_id IN (SELECT tenant_id FROM qualified) GROUP BY tt.tenant_id, tt.gross_eur_fy, tt.refunded_eur_fy ) SELECT t.name AS merchant_name, t.industry AS vertical, ROUND(p.gross_eur_fy, 2) AS gross_captured_eur_fy2025, ROUND(100.0 * p.q1_ref / NULLIF(p.q1_gross, 0), 2) AS refund_rate_q1_pct, ROUND(100.0 * p.q2_ref / NULLIF(p.q2_gross, 0), 2) AS refund_rate_q2_pct, ROUND(100.0 * p.q3_ref / NULLIF(p.q3_gross, 0), 2) AS refund_rate_q3_pct, ROUND(100.0 * p.q4_ref / NULLIF(p.q4_gross, 0), 2) AS refund_rate_q4_pct, ROUND(100.0 * p.refunded_eur_fy / NULLIF(p.gross_eur_fy, 0), 2) AS refund_rate_fy2025_pct FROM pivot p JOIN tenants t ON t.id = p.tenant_id ORDER BY refund_rate_q3_pct DESC NULLS LAST, merchant_name ASC LIMIT 30
STATUS: REJECTED - not a single SELECT statement: syntax error at or near "pivot"
dry_runWITH fx AS ( SELECT quote_code, as_of, rate FROM exchange_rates WHERE base_code = 'EUR' ), base AS ( SELECT p.tenant_id, p.currency_code, p.amount, p.amount_refunded, CAST(p.captured_at AS date) AS captured_date, EXTRACT(QUARTER FROM p.captured_at)::int AS q FROM payments p JOIN tenants t ON t.id = p.tenant_id WHERE (t.industry IS DISTINCT FROM 'Apparel & Footwear') AND p.status IN ('captured', 'refunded', 'partially_refunded') AND p.captured_at >= TIMESTAMP '2025-01-01' AND p.captured_at < TIMESTAMP '2026-01-01' ), converted AS ( SELECT b.tenant_id, b.q, CASE WHEN b.currency_code = 'EUR' THEN b.amount ELSE b.amount / fx.rate END AS amount_eur, CASE WHEN b.currency_code = 'EUR' THEN b.amount_refunded ELSE b.amount_refunded / fx.rate END AS refunded_eur FROM base b LEFT JOIN fx ON fx.quote_code = b.currency_code AND fx.as_of = b.captured_date ), tenant_quarter AS ( SELECT tenant_id, q, SUM(amount_eur) AS gross_eur, SUM(refunded_eur) AS refunded_eur, COUNT(*) AS cnt FROM converted GROUP BY tenant_id, q ), tenant_total AS ( SELECT tenant_id, SUM(gross_eur) AS gross_eur_fy, SUM(refunded_eur) AS refunded_eur_fy, SUM(cnt) AS cnt_fy FROM tenant_quarter GROUP BY tenant_id ), qualified AS ( SELECT tenant_id FROM tenant_total WHERE cnt_fy >= 20 ), pivoted AS ( SELECT tt.tenant_id, tt.gross_eur_fy, tt.refunded_eur_fy, MAX(CASE WHEN tq.q = 1 THEN tq.gross_eur END) AS q1_gross, MAX(CASE WHEN tq.q = 1 THEN tq.refunded_eur END) AS q1_ref, MAX(CASE WHEN tq.q = 2 THEN tq.gross_eur END) AS q2_gross, MAX(CASE WHEN tq.q = 2 THEN tq.refunded_eur END) AS q2_ref, MAX(CASE WHEN tq.q = 3 THEN tq.gross_eur END) AS q3_gross, MAX(CASE WHEN tq.q = 3 THEN tq.refunded_eur END) AS q3_ref, MAX(CASE WHEN tq.q = 4 THEN tq.gross_eur END) AS q4_gross, MAX(CASE WHEN tq.q = 4 THEN tq.refunded_eur END) AS q4_ref FROM tenant_total tt JOIN tenant_quarter tq ON tq.tenant_id = tt.tenant_id WHERE tt.tenant_id IN (SELECT tenant_id FROM qualified) GROUP BY tt.tenant_id, tt.gross_eur_fy, tt.refunded_eur_fy ) SELECT t.name AS merchant_name, t.industry AS vertical, ROUND(p.gross_eur_fy, 2) AS gross_captured_eur_fy2025, ROUND(100.0 * p.q1_ref / NULLIF(p.q1_gross, 0), 2) AS refund_rate_q1_pct, ROUND(100.0 * p.q2_ref / NULLIF(p.q2_gross, 0), 2) AS refund_rate_q2_pct, ROUND(100.0 * p.q3_ref / NULLIF(p.q3_gross, 0), 2) AS refund_rate_q3_pct, ROUND(100.0 * p.q4_ref / NULLIF(p.q4_gross, 0), 2) AS refund_rate_q4_pct, ROUND(100.0 * p.refunded_eur_fy / NULLIF(p.gross_eur_fy, 0), 2) AS refund_rate_fy2025_pct FROM pivoted p JOIN tenants t ON t.id = p.tenant_id ORDER BY refund_rate_q3_pct DESC NULLS LAST, merchant_name ASC LIMIT 30
STATUS: COMPILES (dry run on the empty schema, no data read) COLUMNS: merchant_name, vertical, gross_captured_eur_fy2025, refund_rate_q1_pct, refund_rate_q2_pct, refund_rate_q3_pct, refund_rate_q4_pct, refund_rate_fy2025_pct
submitWITH fx AS ( SELECT quote_code, as_of, rate FROM exchange_rates WHERE base_code = 'EUR' ), base AS ( SELECT p.tenant_id, p.currency_code, p.amount, p.amount_refunded, CAST(p.captured_at AS date) AS captured_date, EXTRACT(QUARTER FROM p.captured_at)::int AS q FROM payments p JOIN tenants t ON t.id = p.tenant_id WHERE (t.industry IS DISTINCT FROM 'Apparel & Footwear') AND p.status IN ('captured', 'refunded', 'partially_refunded') AND p.captured_at >= TIMESTAMP '2025-01-01' AND p.captured_at < TIMESTAMP '2026-01-01' ), converted AS ( SELECT b.tenant_id, b.q, CASE WHEN b.currency_code = 'EUR' THEN b.amount ELSE b.amount / fx.rate END AS amount_eur, CASE WHEN b.currency_code = 'EUR' THEN b.amount_refunded ELSE b.amount_refunded / fx.rate END AS refunded_eur FROM base b LEFT JOIN fx ON fx.quote_code = b.currency_code AND fx.as_of = b.captured_date ), tenant_quarter AS ( SELECT tenant_id, q, SUM(amount_eur) AS gross_eur, SUM(refunded_eur) AS refunded_eur, COUNT(*) AS cnt FROM converted GROUP BY tenant_id, q ), tenant_total AS ( SELECT tenant_id, SUM(gross_eur) AS gross_eur_fy, SUM(refunded_eur) AS refunded_eur_fy, SUM(cnt) AS cnt_fy FROM tenant_quarter GROUP BY tenant_id ), qualified AS ( SELECT tenant_id FROM tenant_total WHERE cnt_fy >= 20 ), pivoted AS ( SELECT tt.tenant_id, tt.gross_eur_fy, tt.refunded_eur_fy, MAX(CASE WHEN tq.q = 1 THEN tq.gross_eur END) AS q1_gross, MAX(CASE WHEN tq.q = 1 THEN tq.refunded_eur END) AS q1_ref, MAX(CASE WHEN tq.q = 2 THEN tq.gross_eur END) AS q2_gross, MAX(CASE WHEN tq.q = 2 THEN tq.refunded_eur END) AS q2_ref, MAX(CASE WHEN tq.q = 3 THEN tq.gross_eur END) AS q3_gross, MAX(CASE WHEN tq.q = 3 THEN tq.refunded_eur END) AS q3_ref, MAX(CASE WHEN tq.q = 4 THEN tq.gross_eur END) AS q4_gross, MAX(CASE WHEN tq.q = 4 THEN tq.refunded_eur END) AS q4_ref FROM tenant_total tt JOIN tenant_quarter tq ON tq.tenant_id = tt.tenant_id WHERE tt.tenant_id IN (SELECT tenant_id FROM qualified) GROUP BY tt.tenant_id, tt.gross_eur_fy, tt.refunded_eur_fy ) SELECT t.name AS merchant_name, t.industry AS vertical, ROUND(p.gross_eur_fy, 2) AS gross_captured_eur_fy2025, ROUND(100.0 * p.q1_ref / NULLIF(p.q1_gross, 0), 2) AS refund_rate_q1_pct, ROUND(100.0 * p.q2_ref / NULLIF(p.q2_gross, 0), 2) AS refund_rate_q2_pct, ROUND(100.0 * p.q3_ref / NULLIF(p.q3_gross, 0), 2) AS refund_rate_q3_pct, ROUND(100.0 * p.q4_ref / NULLIF(p.q4_gross, 0), 2) AS refund_rate_q4_pct, ROUND(100.0 * p.refunded_eur_fy / NULLIF(p.gross_eur_fy, 0), 2) AS refund_rate_fy2025_pct FROM pivoted p JOIN tenants t ON t.id = p.tenant_id ORDER BY refund_rate_q3_pct DESC NULLS LAST, merchant_name ASC LIMIT 30
Submitted to tonight's batch. Your work on this request is done.