{
 "notes": "Reading last night's reports:\n\nReport 1 (Cragsley weekly conversion around the Nov 24 outage) undercuts the simple story: conversion didn't dip during the broken-reminder week — it hit 43.5%, the *highest* week in the whole window, up from a 29-41% range beforehand. The obvious explanation is that Nov 24-30, 2025 is Black Friday/Cyber Monday week — a massive demand spike that would swamp any negative effect from broken reminder emails. So this natural experiment is confounded by timing and can't cleanly tell us whether the reminders matter; I don't think it's worth forcing further at the weekly grain, but a daily cut around the exact outage start (before Black Friday really kicks in on Nov 28) might still show something, so I'll try that once.\n\nReport 2 (price tier vs. conversion) reinforces the Q1 story on a different cut: higher-priced carts (which are also higher-item-count: 1.3 items at <€50 vs 3.2 items at €200+) convert *better and faster* (51.4% / 44.1% within 1hr for €200+ vs 23.3% / 16.1% for <€50) — consistent with last night's finding that small, likely single-item, lower-value carts are where hesitation concentrates, not pricier \"considered\" purchases. Two independent cuts now agree, so I consider Q1 well-answered. Before I put \"small single-item carts stall\" in the memo as a general pattern, I want one quick robustness check that it's not just one merchant (e.g. Cragsley, which dominates volume) driving the aggregate.\n\nReport 3 (email nudge) shows a striking gap — 56.0% eventual conversion for carts whose user got an email vs. 8.1% for no-email — but it's likely confounded: 7,540 of the 12,280 \"no_email\" carts are guest carts that structurally can never receive an email (no user_id to target), and guests plausibly convert worse regardless of email. I want to split \"no_email\" into guest vs. logged-in before trusting this as evidence the nudge itself works, since the fair comparison is received_email vs. logged-in-but-not-emailed.\n\nTonight's 3 requests: (1) the cleaner 3-way email-nudge split, (2) a daily drill-down at Cragsley right at the outage start to see if Black Friday is really masking a real dip, (3) a per-tenant robustness check that the single-item-cart-stalls pattern isn't just one merchant's effect.",
 "requests": [
  {
   "title": "Email nudge effect on stalled carts, controlling for guest vs. logged-in customers",
   "question": "Once we separate carts that could never receive an email (guests) from logged-in customers who simply weren't emailed, does receiving an email still look like it drives recovery?",
   "grain": "one row per group: received an email (logged-in) / logged-in but no email / guest (no user to email)",
   "columns": [
    "group",
    "cart count",
    "pct eventually converted",
    "median days to convert (converted carts only)"
   ],
   "details": "Same population and definitions as the prior 'stalled carts that receive an email' report: the 6 retail tenants (Kibblewick, Studio Vrij, Petalcourt Beauty, Marrowby & Vane, Cragsley Outfitters, Ampfeld Elektronik), carts with created_at in 2025-01-01 to 2025-11-30, restricted to carts not already converted within the first hour of creation. 'received_email' = non-null user_id with at least one email_log row (same tenant_id and user_id) with sent_at between created_at+1h and created_at+48h. 'logged_in_no_email' = non-null user_id with no such email_log row. 'guest' = null user_id (can never be matched to an email). pct_eventually_converted and median_days_to_convert use the same definitions as before. Order rows: received_email, logged_in_no_email, guest.",
   "builds_on": [
    "Do stalled carts that receive an email convert more often?"
   ]
  },
  {
   "title": "Daily cart conversion at Cragsley Outfitters, Nov 17 – Dec 1 2025",
   "question": "Is there a visible conversion dip in the first few days after cart-reminder emails broke (Nov 24), before Black Friday/Cyber Monday demand likely swamps the signal?",
   "grain": "one row per calendar day of cart creation, Cragsley Outfitters only",
   "columns": [
    "date",
    "carts created",
    "overall conversion pct",
    "pct converted within 1 hour"
   ],
   "details": "Tenant: Cragsley Outfitters. Population: carts with created_at on each day from 2025-11-17 through 2025-12-01 inclusive (15 days), bracketing one week before the outage (Nov 17-23) against the outage week and the days just after (Nov 24-Dec 1, including Black Friday Nov 28 and Cyber Monday Dec 1). Use the same overall_conversion_pct and pct_converted_within_1_hour definitions as the prior weekly report. Order rows by date ascending.",
   "builds_on": [
    "Cart conversion by week at Cragsley Outfitters around the Nov 24 reminder-email outage"
   ]
  },
  {
   "title": "Single-item vs. multi-item cart conversion, by tenant",
   "question": "Does the pattern 'small, single-item carts convert worse than multi-item carts' hold consistently across all 6 retail merchants, or is it driven by one or two of them?",
   "grain": "one row per tenant",
   "columns": [
    "tenant name",
    "single-item cart count",
    "single-item conversion pct",
    "multi-item (2+) cart count",
    "multi-item conversion pct",
    "gap in points (multi minus single)"
   ],
   "details": "Tenants: Kibblewick, Studio Vrij, Petalcourt Beauty, Marrowby & Vane, Cragsley Outfitters, Ampfeld Elektronik. Population: carts with created_at in 2025-01-01 to 2025-12-31. Split each tenant's carts into item_count = 1 ('single-item') vs item_count >= 2 ('multi-item') using carts.item_count. conversion pct = share of carts in that group with status='converted', rounded 1 decimal, for each tenant. gap_in_points = multi-item conversion pct minus single-item conversion pct. Order rows by gap in points descending, tie-break by tenant name.",
   "builds_on": [
    "Cart contents: stalled vs. fast-converting carts, 2025",
    "Cart value tier vs. conversion speed, 2025"
   ]
  }
 ]
}