feat: Tier B operator scaffolding — bundle, copy SoT, posts, emails

Pick up and finish yesterday's cut-off Tier B pass.

- build/: PyInstaller scaffold (datatools.spec + launcher.py +
  hook-streamlit.py + README) — folder-mode bundle, locked
  127.0.0.1, per-OS recipe
- marketing/COPY.md: single source of truth for every customer-facing
  string — landing H1/sub/CTAs, demo CTAs, email subjects, Gumroad
  listing, banned phrases
- marketing/community-posts/: 9 drafts (3 posts × 3 niches:
  bookkeeper, revops, shopify-pet) — story / tip / soft-offer
- marketing/emails/: 18 drafts (Gumroad delivery + 5-touch
  onboarding × 3 niches), per-niche segmentation guidance
- docs/NEXT-STEPS.md: flip 2.2 / 2.4 / 3.1 / 3.4 to done with
  pointers to the new assets; add Phase 0 inventory rows
- .gitignore: narrow `build/` ignore so PyInstaller spec + launcher
  + hooks get tracked, only generated artifacts (build/build/,
  build/__pycache__/, build/dist/) stay ignored

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

marketing/emails/shopify-pet/04-day14.md

@@ -0,0 +1,32 @@
+# Shopify-pet · Day 14 — Two-minute trick: hidden-character cleanup
+
+**Subject:** Two-minute trick: hidden-character cleanup
+**Send:** Day 14
+**Goal:** surface the text cleaner — non-obvious, high-value
+
+---
+
+Hi {{first_name}},
+
+The tool inside DataTools that buyers find last is the **text cleaner** — and on Shopify customer exports it's usually the one with the most "wait, that was a problem?" moments.
+
+What it catches: invisible characters that got into your customer data when customers typed on their phones. The most common offenders:
+
+- **Zero-width space** (`U+200B`) inside emails — Klaviyo treats `s​arah@acme.com` (with hidden char) and `sarah@acme.com` (without) as different addresses
+- **Non-breaking space** (`U+00A0`) inside addresses — Shopify accepts it, Klaviyo accepts it, but USPS address validation fails on it
+- **BOM marker** (`U+FEFF`) at the start of CSV cells — usually from a customer pasting from Word or a PDF
+- **Right-to-left mark** (`U+200F`) — rare, but appears in customer names from Hebrew/Arabic locales
+
+The 2-minute workflow:
+
+1. After the format standardizer pass, run the text cleaner.
+2. It produces an additional sidecar file: `<filename>.hidden-chars.csv` — every cell where it found a hidden char, with a "what was hidden where" annotation.
+3. Skim it. Most are fine to silently strip (zero-width spaces, BOMs). For rare ones (right-to-left marks in a name), confirm before stripping — sometimes they're load-bearing.
+4. Click "Apply cleanup". The text cleaner replaces the hidden chars in the cleaned CSV.
+
+The reason this matters: **dedupe runs after text-clean.** Two emails with a hidden char difference look identical in the GUI but get treated as two separate customers — and your dedupe pass won't catch them unless the text cleaner ran first.
+
+The pipeline order baked into the GUI is: `analyzer → format → text-clean → dedupe → gate`. Stick to it; per-tool runs out of order are the most common source of "wait, why didn't dedupe catch this?".
+
+— Michael
+{{support_email}}